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Schomaker, Prof. Lambert

Lambert Schomaker
Lambert Schomaker

Lambert Schomaker is professor of Artificial Intelligence and scientific director of the research institute ALICE (Artificial Intelligence & Cognitive Engineering). He has worked on several projects concerning the recognition of online, connected cursive script on the basis of knowledge of the handwriting movement process. Current projects are in the area of image-based retrieval, online and offline handwriting recognition, forensic writer identification, and cognitive robot navigation models. His work on neural networks for handwriting and gesture recognition was a precursor to modern handwriting and gesture-recognition methods on tablet computers such as the iPad.

He is currently active in a multidisciplinary project (Target) for mass-storage, high-performance computing and datamining, in order to implement the Monk generic search engine for handwritten historical archives. The Monk system is unique in the world due to its huge scale, genericity and its use of live, '24/7', machine learning. In another project (Mantis), Schomaker is using robustness principles from AI to develop smart systems that can detect and solve problems along industrial assembly lines.

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Publications

2020

Maillette de Buy Wenniger, G., van Dongen, T., Aedmaa, E., Teun Kruitbosch, H., Valentijn, E. A., & Schomaker, L. (2020). Structure-Tags Improve Text Classification for Scholarly Document Quality Prediction. Manuscript submitted for publication.
He, S., & Schomaker, L. (2020). FragNet: Writer Identification using Deep Fragment Networks. IEEE transactions on information forensics and security. https://doi.org/10.1109/TIFS.2020.2981236
Dhali, M. A., Jansen, C. N., De Wit, J. W., & Schomaker, L. (2020). Feature-extraction methods for historical manuscript dating based on writing style development. Pattern Recognition Letters, 131, 413-420. https://doi.org/10.1016/j.patrec.2020.01.027
Oosterhuis, T., & Schomaker, L. (2020). "Who is Driving around Me?": Unique Vehicle Instance Classification using Deep Neural Features. ArXiv.
Li, Y., Schomaker, L., & Kasaei, S. H. (2020). Learning to Grasp 3D Objects using Deep Residual U-Nets. ArXiv.
Luo, S., Kasaei, H., & Schomaker, L. (2020). Accelerating Reinforcement Learning for Reaching using Continuous Curriculum Learning. ArXiv.

2019

Schomaker, L. (2019). Lifelong learning for text retrieval and recognition in historical handwritten document collections. Manuscript submitted for publication.
Ameryan, M., & Schomaker, L. (2019). A limited-size ensemble of homogeneous CNN/LSTMs for high-performance word classification. Manuscript submitted for publication.
Dhali, M. A., Wit, J. W. D., & Schomaker, L. (2019). BiNet: Degraded-Manuscript Binarization in Diverse Document Textures and Layouts using Deep Encoder-Decoder Networks. ArXiv.
He, S., & Schomaker, L. (2019). DeepOtsu: Document enhancement and binarization using iterative deep learning. Pattern recognition, 91, 379-390. https://doi.org/10.1016/j.patcog.2019.01.025
Sriman, B., & Schomaker, L. (2019). Multi-script text versus non-text classification of regions in scene images. Journal of Visual Communication and Image Representation, 62, 23-42. https://doi.org/10.1016/j.jvcir.2019.04.007
Schomaker, L. (2019). A large-scale field test on word-image classification in large historical document collections using a traditional and two deep-learning methods. ArXiv. https://doi.org/10.13140/RG.2.2.11940.53120
He, S., & Schomaker, L. (2019). Deep adaptive learning for writer identification based on single handwritten word images. Pattern recognition, 88, 64-74. https://doi.org/10.1016/j.patcog.2018.11.003
Wenniger, G. M. D. B., Schomaker, L., & Way, A. (2019). No Padding Please: Efficient Neural Handwriting Recognition. In 2019 International Conference on Document Analysis and Recognition (ICDAR) (pp. 355-362). IEEE. https://doi.org/10.1109/ICDAR.2019.00064
Sillitti, A., Schomaker, L., Anakabe, J. F., Basurko, J., Dam, P., Ferreira, H., ... Zurutuza, U. (2019). Providing Proactiveness: Data Analysis Techniques Portfolios. In M. Albano, E. Jantunen, G. Papa, & U. Zurutuza (Eds.), The MANTIS Book : Cyber Physical System Based Proactive Collaborative Maintenance (pp. 145-238). Gistrup (DK): River Publishers.
Dijkstra, K., van de Loosdrecht, J., Schomaker, L. R. B., & Wiering, M. A. (2019). CentroidNet: A Deep Neural Network for Joint Object Localization and Counting. In U. Brefeld, E. Curry, E. Daly, B. MacNamee, A. Marascu, F. Pinelli, M. Berlingerio, ... N. Hurly (Eds.), ECML PKDD 2018: Machine Learning and Knowledge Discovery in Databases (pp. 585-601). ( Lecture Notes in Computer Science; Vol. 11053). Cham: Springer. https://doi.org/10.1007/978-3-030-10997-4_36
Schomaker, L., Albano, M., Jantunen, E., & Ferreira, L. L. (2019). The future of Maintenance. In M. Albano, E. Jantunen, G. Papa, & U. Zurutuza (Eds.), The MANTIS Book : Cyber Physical System Based Proactive Collaborative Maintenance (pp. 555). Gistrup (DK): River Publishers.
Steging, C., Schomaker, L., & Verheij, B. (2019). The Xai paradox: Systems that perform well for the wrong reasons. Paper presented at BNAIC/Benelearn Conference, Brussels, Belgium.

2018

Chanda, S., Baas, J., Haitink, D., Hamel, S., Stutzmann, D., & Schomaker, L. (2018). Zero-shot learning based approach for medieval word recognition using deep-learned features. In Proceedings of International Conference on Frontiers in Handwriting Recognition, ICFHR (pp. 345-350). (Proceedings of International Conference on Frontiers in Handwriting Recognition, ICFHR; Vol. 2018-August). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICFHR-2018.2018.00067
Okafor, E., Berendsen, G., Schomaker, L., & Wiering, M. (2018). Detection and Recognition of Badgers Using Deep Learning. In V. Kurkova, Y. Manolopoulos, B. Hammer, L. Iliadis, & I. Maglogiannis (Eds.), International Conference on Artificial Neural Networks (pp. 554-563). (Lecture Notes in Computer Science book series; Vol. 11141). Springer International Publishing, Cham, Switzerland. https://doi.org/10.1007/978-3-030-01424-7_54
He, S., & Schomaker, L. (2018). Open Set Chinese Character Recognition using Multi-typed Attributes. ArXiv.
Dijkstra, K., van de Loosdrecht, J., Schomaker, L. R. B., & Wiering, M. A. (2018). Hyperspectral demosaicking and crosstalk correction using deep learning. Machine Vision and Applications, 30(1). https://doi.org/10.1007/s00138-018-0965-4
Chanda, S., Okafor, E., Hamel, S., Stutzmann, D., & Schomaker, L. (2018). Deep Learning for Classification and as Tapped-Feature Generator in Medieval Word-Image Recognition. In 13th IAPR International Workshop on Document Analysis Systems (DAS) (pp. 217-222). IEEE. https://doi.org/10.1109/DAS.2018.82
Weber, A., Ameryan, M., Wolstencroft, K., Stork, L., Heerlien, M., & Schomaker, L. (2018). Towards a Digital Infrastructure for Illustrated Handwritten Archives. In M. Ioannides (Ed.), Lecture Notes in Computer Science, vol. 10605: Final Conference of the Marie Skłodowska-Curie Initial Training Network for Digital Cultural Heritage, ITN-DCH 2017, Olimje, Slovenia (pp. 155-166). Springer. https://doi.org/10.1007/978-3-319-75826-8_13
Bidoia, F., Sabatelli, M., Shantia, A., Wiering, M. A., & Schomaker, L. (2018). A Deep Convolutional Neural Network for Location Recognition and Geometry based Information. In M. De Marsico, G. Sanniti di Baja, & A. Fred (Eds.), Proceedings of the 7th International Conference on Pattern Recognition Applications and Methods (pp. 27-36). SciTePress. https://doi.org/10.5220/0006542200270036
Okafor, E., Schomaker, L., & Wiering, M. A. (2018). An analysis of rotation matrix and colour constancy data augmentation in classifying images of animals. Journal of Information and Telecommunication, 2(4), 465-491. https://doi.org/10.1080/24751839.2018.1479932
van de Wolfshaar, J., Wiering, M., & Schomaker, L. (2018). Deep Learning Policy Quantization. In Proceedings of the 10th International Conference on Agents and Artificial Intelligence (pp. 122-130). SciTePress. https://doi.org/10.5220/0006592901220130
Okafor, E., & Schomaker, L. (2018). Integrated Dimensionality Reduction and Sequence Prediction using LSTM. Poster session presented at ICT.Open, Amersfoort, Netherlands.

2017

Pawara, P., Okafor, E., Schomaker, L., & Wiering, M. (2017). Data Augmentation for Plant Classification. In Advanced Concepts for Intelligent Vision Systems (Acivs 2017) [112]
Okafor, E., Smit, R., Schomaker, L., & Wiering, M. (2017). Operational Data Augmentation in Classifying Single Aerial Images of Animals. In IEEE International Conference on INnovations in Intelligent SysTems and Applications (INISTA), 2017 (pp. 354-360). IEEE. https://doi.org/10.1109/INISTA.2017.8001185
Valentijn, E. A., Begeman, K., Belikov, A., Boxhoorn, D. R., Brinchmann, J., McFarland, J., ... van Dijk, G. J. W. (2017). Target and (Astro-)WISE technologies - Data federations and its applications. In Astroinformatics 2017 (pp. 333-340). (Proceedings IAU Symposium; Vol. 12, issue S325, Astroinformatics). International Astronomical Union. https://doi.org/10.1017/S1743921317000254
Dijkstra, K., van de Loosdrecht, J., Schomaker, L., & Wiering, M. (2017). Hyper-spectral frequency selection for the classification of vegetation diseases. In European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (2017 ed., pp. 483-488). Bruges (Belgium): ESANN.
He, S., & Schomaker, L. (2017). Beyond OCR: Multi-faceted understanding of handwritten document characteristics. Pattern recognition, 63, 321-333. https://doi.org/10.1016/j.patcog.2016.09.017
Shantia, A., Bidoia, F., Schomaker, L., & Wiering, M. (2017). Dynamic Parameter Update for Robot Navigation Systems through Unsupervised Environmental Situational Analysis. In IEEE Symposium Series on Computational Intelligence (pp. 1-7). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SSCI.2016.7850238
Okafor, E., Pawara, P., Karaaba, M., Surinta, O., Codreanu, V., Schomaker, L., & Wiering, M. (2017). Comparative study between deep learning and bag of visual words for wild-animal recognition. In 2016 IEEE Symposium Series on Computational Intelligence, SSCI 2016 (2016 IEEE Symposium Series on Computational Intelligence, SSCI 2016). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SSCI.2016.7850111
He, S., & Schomaker, L. (2017). Co-occurrence features for writer identification. In Proceedings of International Conference on Frontiers in Handwriting Recognition, ICFHR (pp. 78-83). (Proceedings of International Conference on Frontiers in Handwriting Recognition, ICFHR). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICFHR.2016.0027
Pawara, P., Okafor, E., Surinta, O., Schomaker, L., & Wiering, M. (2017). Comparing local descriptors and bags of visualwords to deep convolutional neural networks for plant recognition. In A. Fred, M. D. De Marsico, & G. S. di Baja (Eds.), ICPRAM 2017 - Proceedings of the 6th International Conference on Pattern Recognition Applications and Methods (pp. 479-486). SciTePress.
Dhali, M., He, S., Popovic, M., Tigchelaar, E., & Schomaker, L. (2017). A Digital Palaeographic Approach towards Writer Identification in the Dead Sea Scrolls. In Proceedings of the 6th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, 693-702, 2017, Porto, Portugal (pp. 693-702) https://doi.org/10.5220/0006249706930702
Pawara, P., Okafor, E., Surinta, O., Schomaker, L., & Wiering, M. (2017). Comparing Local Descriptors and Bags of Visual Words to Deep Convolutional Neural Networks for Plant Recognition. In 6th International Conference on Pattern Recognition Applications and Methods (ICPRAM 2017) ICPRAM .
He, S., & Schomaker, L. (2017). Writer identification using curvature-free features. Pattern recognition, 63, 451-464. https://doi.org/10.1016/j.patcog.2016.09.044

2016

He, S., Samara, P., Burgers, J., & Schomaker, L. (2016). A Multiple-Label Guided Clustering Algorithm for Historical Document Dating and Localization. Ieee transactions on image processing, 25(11), 5252-5265. https://doi.org/10.1109/TIP.2016.2602078
He, S., Samara, P., Burgers, J., & Schomaker, L. (2016). Historical manuscript dating based on temporal pattern codebook. Computer Vision and Image Understanding, 152, 167-175. https://doi.org/10.1016/j.cviu.2016.08.008
He, S., Samara, P., Burgers, J., & Schomaker, L. (2016). Image-based historical manuscript dating using contour and stroke fragments. Pattern recognition, 58, 159-171. https://doi.org/10.1016/j.patcog.2016.03.032
Sriman, B., Schomaker, L., & Pruksasri, P. (2016). General Text-Chunk Localization in Scene Images using a Codebook-based Classifier. In Proceedings of the 4th IIAE International Conference on Intelligent Systems and Image Processing 2016 (pp. 134-141). IEEE.
Schomaker, L. (2016). Caveats on Bayesian and hidden-Markov models (v2.8). Manuscript submitted for publication.
He, S., & Schomaker, L. (2016). General Pattern Run-Length Transform for Writer Identification. In Proceedings - 12th IAPR International Workshop on Document Analysis Systems, DAS 2016 (pp. 60-65). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/DAS.2016.42
Bhowmik, T. K., Parui, S. K., Roy, U., & Schomaker, L. (2016). Bangla Handwritten Character Segmentation Using Structural Features: A Supervised and Bootstrapping Approach. ACM Transactions on Asian and Low-Resource Language Information Processing, 15(4), 29:1-29:26. [29]. https://doi.org/10.1145/2890497
Niitsuma, M., Schomaker, L., van Oosten, J-P., Tomita, Y., & Bell, D. (2016). Musicologist-driven writer identification in early music manuscripts. Multimedia Tools and Applications, 75(11), 6463-6479. https://doi.org/10.1007/s11042-015-2583-8
Okafor, E., Pawara, P., Karaaba, M., Surinta, O., Codreanu, V., Schomaker, L., & Wiering, M. (2016). Comparative Study Between Deep Learning and Bag of Visual Words for Wild-Animal Recognition. In IEEE Symposium Series on Computational Intelligence Athens, Greece: IEEE.
He, S., Samara, P., Burgers, J., & Schomaker, L. (2016). Discovering visual element evolutions for historical document dating. In 2016 15th International Conference on Frontiers in Handwriting Recognition (ICFHR) (pp. 7-12). IEEE (The Institute of Electrical and Electronics Engineers).
Schimbinschi, F., Schomaker, L., & Wiering, M. (2016). Ensemble methods for robust 3D face recognition using commodity depth sensors. In IEEE Symposium Series on Computational Intelligence: Symposium on Computational Intelligence in Biometrics and Identity Management (Proceedings - 2015 IEEE Symposium Series on Computational Intelligence, SSCI 2015). IEEE (The Institute of Electrical and Electronics Engineers). https://doi.org/10.1109/SSCI.2015.36
He, S., Samara, P., Burgers, J., & Schomaker, L. (2016). Historical Document Dating Using Unsupervised Attribute Learning. In 2016 12th IAPR Workshop on Document Analysis Systems (DAS) (pp. 36-44). IEEE (The Institute of Electrical and Electronics Engineers).

2015

Schomaker, L. (2016). Design considerations for a large-scale image-based text search engine in historical manuscript collections. Information Technology, 58(2), 80-88. https://doi.org/10.1515/itit-2015-0049
Karaaba, M., Surinta, O., Schomaker, L., & Wiering, M. (2015). Robust Face Recognition by Computing Distances from Multiple Histograms of Oriented Gradients. In IEEE Symposium Series on Computational Intelligence: Symposium on Computational Intelligence in Biometrics and Identity Management IEEE (The Institute of Electrical and Electronics Engineers).
He, S., Wiering, M., & Schomaker, L. (2015). Junction detection in handwritten documents and its application to writer identification. Pattern recognition, 48(12), 4036-4048. https://doi.org/10.1016/j.patcog.2015.05.022
Sriman, B., & Schomaker, L. (2015). Explicit Foreground and Background Modeling in The Classification of Text Blocks in Scene Images. In Proceedings of a meeting held 3-6 November 2015, Kuala Lumpur, Malaysia (Vol. 1, pp. 830). [234] IEEE.
Surinta, O., Karaaba, M. F., Schomaker, L. R. B., & Wiering, M. A. (2015). Recognition of handwritten characters using local gradient feature descriptors. Engineering Applications of Artificial Intelligence, 45, 405-414. https://doi.org/10.1016/j.engappai.2015.07.017
Sriman, B., & Schomaker, L. (2015). Object Attention Patches for Text Detection and Recognition in Scene Images using SIFT. In M. De Marsico, M. Figueiredo, & A. Fred (Eds.), In Proceedings of the International Conference on Pattern Recognition Applications and Methods: ICPRAM 2015 (Vol. 1, pp. 304-311). Lisbon, Portugal: SciTePress. https://doi.org/10.5220/0005218603040311
He, S., & Schomaker, L. (2015). A Polar Stroke Descriptor for Classification of Historical Documents. In 13th International Conference on Document Analysis and Recognition (ICDAR) (pp. 6-10). IEEE (The Institute of Electrical and Electronics Engineers).
Shantia, A., Timmers, R., Schomaker, L., & Wiering, M. (2015). Indoor Localization by Denoising Autoencoders and Semi-supervised Learning in 3D Simulated Environment. In International Joint Conference on Neural Networks IEEE (The Institute of Electrical and Electronics Engineers). https://doi.org/10.1109/IJCNN.2015.7280715
Karaaba, M., Surinta, O., Schomaker, L., & Wiering, M. (2015). In-Plane Rotational Alignment of Faces by Eye and Eye-Pair Detection. In 11th International Conference on Computer Vision Theory and Applications
Surinta, O., Karaaba, M., Mishra, T. K., Schomaker, L., & Wiering, M. (2015). Recognizing Handwritten Characters with Local Descriptors and Bags of Visual Words. In L. Iliadis, & C. Jayne (Eds.), Engineering Applications of Neural Networks (EANN): 16th International Conference on Engineering Applications of Neural Networks, Proceedings (pp. 255-264). (Communications in computer and information science; Vol. 517). Springer.

2014

Surinta, O., Karaaba, M., van Oosten, J-P., Schomaker, L., & Wiering, M. (2014). A* Path Planning for Line Segmentation of Handwritten Documents. In International Conference on Frontiers in Handwriting Recognition (ICFHR) (pp. 175-180). IEEE (The Institute of Electrical and Electronics Engineers). https://doi.org/10.1109/ICFHR.2014.37
Karaaba, M. F., Schomaker, L., & Wiering, M. (2014). Machine learning for multi-view eye-pair detection. Engineering Applications of Artificial Intelligence, 33, 69-79. https://doi.org/10.1016/j.engappai.2014.04.008
van Oosten, J-P., & Schomaker, L. (2014). Separability versus prototypicality in handwritten word-image retrieval. Pattern recognition, 47(3), 1031-1038. https://doi.org/10.1016/j.patcog.2013.09.006
van Oosten, J-P., & Schomaker, L. (2014). A Reevaluation and Benchmark of Hidden Markov Models. In 14th International Conference on Frontiers in Handwriting Recognition (pp. 531-536). [95] https://doi.org/10.1109/ICFHR.2014.95
He, S., & Schomaker, L. (2014). Delta-n Hinge: rotation-invariant features for writer identification. In 22th International Conference on Pattern Recognition(ICPR) (pp. 2023-2028). IEEE (The Institute of Electrical and Electronics Engineers). https://doi.org/10.1109/ICPR.2014.353
Codreanu, V., Droge, B., Williams, D., Yasar, B., Yang, F., Liu, B., ... Wiering, M. (2014). Evaluating automatically parallelized versions of the support vector machine. Concurrency and Computation. https://doi.org/10.1002/cpe
Wiering, M., & Schomaker, L. (2014). Multi-Layer Support Vector Machines. In Regularization, Optimization, Kernels, and Support Vector Machines: Edition: CRC Machine Learning and Pattern Recognition Series (pp. 457-476). [20] Chapman & Hall/CRC Press.
He, S., Samara, P., Burgers, J., & Schomaker, L. (2014). Towards style-based dating of historical documents. In 14th International Conference on Frontiers in Handwritten Recognition https://doi.org/10.1109/ICFHR.2014.52

2013

Surinta, O., Schomaker, L., & Wiering, M. (2013). A Comparison of Feature and Pixel-Based Methods for Recognizing Handwritten Bangla Digits. In International Conference on Document Analysis and Recognition (ICDAR) (pp. 165-169). IEEE (The Institute of Electrical and Electronics Engineers). https://doi.org/10.1109/ICDAR.2013.40
Wiering, M., Schutten, M., Millea, A., Meijster, A., & Schomaker, L. (2013). Deep Support Vector Machines for Regression Problems. In International Workshop on Advances in Regularization, Optimization, Kernel Methods, and Support Vector Machines: theory and applications (pp. 53-54). Leuven.
van der Zant, T., Kouw, M., & Schomaker, L. (2013). Generative Artificial Intelligence: Philosophy and Theory of Artificial Intelligence. In V. C. Mueller (Ed.), Philosophy and Theory of Artificial Intelligence (Vol. 5, pp. 107-120). (Studies in Applied Philosophy, Epistemology and Rational Ethics; Vol. 5). Berlin: Springer. https://doi.org/10.1007/978-3-642-31674-6_8
Wiering, M., van der Ree, M., Embrechts, M., Stollenga, M., Meijster, A., Nolte, A., & Schomaker, L. (2013). The Neural Support Vector Machine. In The 25th Benelux Artificial Intelligence Conference (BNAIC)
Niitsuma, M., Schomaker, L., van Oosten, J-P., & Tomita, Y. (2013). Writer Identification in Old Music Manuscripts Using Contour-Hinge Feature and Dimensionality Reduction with an Autoencoder: Computer Analysis of Images and Patterns. In R. Wilson, E. Hancock, A. Bors, & W. Smith (Eds.), Computer Analysis of Images and Patterns; part 2 (pp. 555-562). (Lecture Notes in Computer Science; Vol. 8048). Springer. https://doi.org/10.1007/978-3-642-40246-3_69

2012

van Oosten, J-P., & Schomaker, L. (2012). Separability versus Prototypicality in Handwritten Word Retrieval. In Frontiers in Handwriting Recognition (ICFHR), 2012 International Conference on (pp. 8-13). IEEE (The Institute of Electrical and Electronics Engineers). https://doi.org/10.1109/ICFHR.2012.269
Brink, A. A., Smit, J., Bulacu, M. L., & Schomaker, L. R. B. (2012). Writer identification using directional ink-trace width measurements. Pattern recognition, 45(1), 162-171. https://doi.org/10.1016/j.patcog.2011.07.005
Ritsema van Eck, M., & Schomaker, L. (2012). Formal Semantic Modeling for Human and Machine-based Decoding of Medieval Manuscripts. In Proceedings of Digital Humanities Hamburg.
Surinta, O., Schomaker, L., & Wiering, M. (2012). Handwritten Character Classification using the Hotspot Feature Extraction Technique. In International Conference on Pattern Recognition Applications and Methods (ICPRAM) (pp. 261-264). INSTICC publishing. https://doi.org/10.5220/0003712002610264

2011

Wiering, M. A., Van Hasselt, H., Pietersma, A., & Schomaker, L. (2011). Reinforcement learning algorithms for solving classification problems. In Proceedings of the 2011 IEEE Symposium On Adaptive Dynamic Programming And Reinforcement Learning (pp. 91-96) https://doi.org/10.1109/ADPRL.2011.5967372
Kootstra, G., de Boer, B., & Schomaker, L. (2011). Predicting Eye Fixations on Complex Visual Stimuli Using Local Symmetry. Cognitive computation, 3(1), 223-240. https://doi.org/10.1007/s12559-010-9089-5
Brink, A. A., Niels, R. M. J., van Batenburg, R. A., van den Heuvel, C. E., & Schomaker, L. R. B. (2011). Towards robust writer verification by correcting unnatural slant. Pattern Recognition Letters, 32(3), 449-457. https://doi.org/10.1016/j.patrec.2010.10.010
Pietersma, A-D., Schomaker, L., & Wiering, M. (2011). Kernel Learning in Support Vector Machines using Dual-Objective Optimization. In Belgian Dutch Artificial Intelligence Conference: BNAIC
Bhowmik, T. K., van Oosten, J-P., & Schomaker, L. (2011). Segmental K-Means Learning with Mixture Distribution for HMM Based Handwriting Recognition. In SO. Kuznetsov, DP. Mandal, MK. Kundu, & SK. Pal (Eds.), PATTERN RECOGNITION AND MACHINE INTELLIGENCE (pp. 432-439). (Lecture Notes in Computer Science; Vol. 6744). BERLIN: Springer.

2009

van der Zant, T., Schomaker, L., Zinger, S., & van Schie, H. (2009). Where are the Search Engines for Handwritten Documents? Interdisciplinary Science Reviews, 34(2-3), 224-235. https://doi.org/10.1179/174327909X441126
Kootstra, G., & Schomaker, L. (2009). Prediction of human eye fixations using symmetry. 56-61.
Bulacu, M., Brink, A., Zant, T. V. D., & Schomaker, L. (2009). Recognition of handwritten numerical fields in a large single-writer historical collection. 808-812. 2009 10th International Conference on Document Analysis and Recognition, Barcelona, Spain, United Kingdom. https://doi.org/10.1109/ICDAR.2009.8
Kootstra, G., de Jong, S., & Schomaker, L. R. B. (2009). Using Local Symmetry for Landmark Selection. In M. Fritz, B. Schiele, & JH. Piater (Eds.), COMPUTER VISION SYSTEMS, PROCEEDINGS (pp. 94-103). (Lecture Notes in Computer Science; Vol. 5815). BERLIN: Springer.
Kootstra, G., & Schomaker, L. (2009). Using Symmetrical Regions of Interest to Improve Visual SLAM. In 2009 IEEE-RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (pp. 930-935). NEW YORK: IEEE (The Institute of Electrical and Electronics Engineers).

2008

van der Zant, T., Schomaker, L., & Haak, K. (2008). Handwritten-word spotting using biologically inspired features. Ieee transactions on pattern analysis and machine intelligence, 30(11), 1945-1957. https://doi.org/10.1109/TPAMI.2008.144
van der Zant, T., Schomaker, L., & Valentijn, E. (2008). Large scale parallel document image processing. In BA. Yanikoglu, & K. Berkner (Eds.), Document recognition and retrieval XV (Vol. 6815). (Proceedings of SPIE; Vol. 6815). BELLINGHAM: SPIE - INT SOC OPTICAL ENGINEERING. https://doi.org/10.1117/12.765482
Brink, A., van der Klauw, H., & Schomaker, L. (2008). Automatic removal of crossed-out handwritten text and the effect on writer verification and identification. In BA. Yanikoglu, & K. Berkner (Eds.), DOCUMENT RECOGNITION AND RETRIEVAL XV (Proceedings of SPIE; Vol. 6815). BELLINGHAM: SPIE - INT SOC OPTICAL ENGINEERING.
Brink, A., Bulacu, M., & Schomaker, L. (2008). How Much Handwritten Text Is Needed for Text-Independent Writer Verification and Identification. In 19TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION, VOLS 1-6 (pp. 2519-2522). (INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION). NEW YORK: IEEE (The Institute of Electrical and Electronics Engineers).
van der Zant, T., Schomaker, L., & Brink, A. (2008). Interactive Evolutionary Computing for the binarization of degenerated handwritten images. In BA. Yanikoglu, & K. Berkner (Eds.), DOCUMENT RECOGNITION AND RETRIEVAL XV (Proceedings of SPIE; Vol. 6815). BELLINGHAM: SPIE - INT SOC OPTICAL ENGINEERING.
Schomaker, L. R. B. (2008). Word mining in a sparsely-labeled handwritten collection. In BA. Yanikoglu, & K. Berkner (Eds.), DOCUMENT RECOGNITION AND RETRIEVAL XV (Proceedings of SPIE; Vol. 6815). BELLINGHAM: SPIE - INT SOC OPTICAL ENGINEERING.
Schomaker, L. (2008). Writer identification and verification. In N. Ratha, & V. Govindaraju (Eds.), Advances in Biometrics: Sensors, Systems and Algorithms (pp. 247-264). (Advances in Biometrics: Sensors, Algorithms and Systems). Springer. https://doi.org/10.1007/978-1-84628-921-7_13

2007

Schomaker, L. R. B. (2007, Sep 26). Advances in Writer Identification and Verification. https://doi.org/10.1109/ICDAR.2007.4377119
Schomaker, L. R. B., Franke, K., & Bulacu, M. L. (2007). Using codebooks of fragmented connected-component contours in forensic and historic writer identification. Pattern Recognition Letters, 28(6), 719-727. https://doi.org/10.1016/j.patrec.2006.08.005
Bulacu, M. L., & Schomaker, L. R. B. (2007). Text-independent writer identification and verification using textural and allographic features. Ieee transactions on pattern analysis and machine intelligence, 29(4), 701-717. https://doi.org/10.1109/TPAMI.2007.1009
Niels, R., Vuurpijl, L., & Schomaker, L. R. B. (2007). Automatic allograph matching in forensic writer identification. International Journal of Pattern Recognition and Artificial Intelligence, 21(1), 61-81. https://doi.org/10.1142/s0218001407005302
Schomaker, L. R. B. (2007). Advances in Writer Identification and Verification. In Proc. of 9th Int. Conf. on Document Analysis and Recognition (ICDAR 2007) (Vol. 2, pp. 1268 - 1273). (IEEE Computer Society).
Bulacu, M. L., & Schomaker, L. R. B. (2007). Automatic handwriting identification on medieval documents. In Proc. of 14th Int. Conf. on Image Analysis and Processing (Vol. 2, pp. 279-284). (IEEE Computer Society). LOS ALAMITOS: IEEE (The Institute of Electrical and Electronics Engineers).
Zinger, S., Nerbonne, J., Schomaker, L. R. B., & van Schie, H. (2007). Content-based text line comparison for historical document retrieval. In P. Osenova, E. Hinrichs, & J. Nerbonne (Eds.), Proceedings of Computational Phonology workshop, Recent Advances in Natural Language Processing conference (pp. 79 - 84). Shoumen, Bulgaria: INCOMA Ltd..
Bulacu, M., van Koert, R., Schomaker, L. R. B., & van der Zant, T. (2007). Layout analysis of handwritten historical documents for searching the archive of the cabinet of the Dutch Queen. In B. Werner (Ed.), ICDAR 2007: NINTH INTERNATIONAL CONFERENCE ON DOCUMENT ANALYSIS AND RECOGNITION, VOLS I AND II, PROCEEDINGS (pp. 357-361). LOS ALAMITOS: IEEE (The Institute of Electrical and Electronics Engineers).
Schomaker, L. R. B. (2007). Reading Systems: An introduction to Digital Document Processing. In B. B. Chaudhuri (Ed.), Digital Document Processing (pp. 1-28). Guildford, Surrey, UK: Springer.
Schomaker, L. R. B. (2007). Retrieval of handwritten lines in historical documents. In Proc. of 9th Int. Conf. on Document Analysis and Recognition (ICDAR 2007) (Vol. 2, pp. 594 - 598). (IEEE Computer Society).
Bulacu, M. L., Schomaker, L. R. B., & Brink, A. A. (2007). Text-independent writer identification and verification on offline Arabic handwriting. In B. Werner (Ed.), ICDAR 2007: NINTH INTERNATIONAL CONFERENCE ON DOCUMENT ANALYSIS AND RECOGNITION, VOLS I AND II, PROCEEDINGS (Vol. 2, pp. 769-773). (IEEE Computer Society). LOS ALAMITOS: IEEE (The Institute of Electrical and Electronics Engineers).
Brink, A., Schomaker, L., & Bulacu, M. (2007). Towards explainable writer verification and identification using vantage writers. In B. Werner (Ed.), ICDAR 2007: NINTH INTERNATIONAL CONFERENCE ON DOCUMENT ANALYSIS AND RECOGNITION, VOLS I AND II, PROCEEDINGS (Vol. 2, pp. 824-828). LOS ALAMITOS: IEEE (The Institute of Electrical and Electronics Engineers).

2006

van der Zant, T., Schomaker, L., Wiering, M., & Brink, A. (2006). Cognitive developmental pattern recognition: Learning to learn. In Proceedings of 'Systems, Man, and Cybernetics' 2006 (pp. 1208-1213). (IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS, CONFERENCE PROCEEDINGS). Taipei, Taiwan: IEEE (The Institute of Electrical and Electronics Engineers).
Bulacu, M. L., & Schomaker, L. R. B. (2006). Combining multiple features for text-independent writer identification and verification. In G. Lorette (Ed.), Proceedings of the tenth International Workshop on Frontiers in Handwriting Recognition (IWFHR 2006) (unknown / not applicable / onbekend / n.v.t.).
Nerbonne, J., & Schomaker, L. R. B. (2006). Poster: Catch project Scratch: Script Analysis Tools for Cultural Heritage. Statistics on Queries and Line Matching. http://www.let.rug.nl/nerbonne/papers/zinger-nerbonne-siren2006_poster.pdf.
Schomaker, L. R. B. (2006). Reading Systems: An introduction to Digital Document Processing. In B. B. Chaudhuri (Ed.), Digital Document Processing
Lorette, G., Bunke, H., Schomaker, L., Université de Rennes 1, IRCCyN, Institut de recherche en informatique et systèmes aléatoires (Rennes), ... PSI (2006). Tenth international workshop on frontiers in handwriting recognition. Finlande: Publisoft.

2005

Bulacu, M. L., & Schomaker, L. R. B. (2005). A comparison of clustering methods for writer identification and verification. In Proceedings of the 8th International Conference on Document Analysis and Recognition (ICDAR 2005) (Vol. II, pp. 1275-1279). Piscataway: IEEE (The Institute of Electrical and Electronics Engineers).
Bulacu, M., & Schomaker, L. (2005). Analysis of texture and connected-component contours for the automatic identification of writers. (pp. 371-372). s.n.
Ezaki, N., Kiyota, K., Bulacu, M. L., & Schomaker, L. R. B. (2005). Improved text-detection methods for a camera-based text reading system for blind persons. In Proceedings of the 8th International Conference on Document Analysis and Recognition (ICDAR 2005) (Vol. 1, pp. 257 - 261). Seoul.
Franke, K., Schomaker, L., & Koppen, M. (2005). Pen force emulating robotic writing device and its application. In Pen force emulating robotic writing device and its application (pp. 36-46). (2005 IEEE Workshop on Advanced Robotics and its Social Impacts; Vol. 2005). IEEE (The Institute of Electrical and Electronics Engineers). https://doi.org/10.1109/ARSO.2005.1511616
Franke, K., & Schomaker, L. R. B. (2005). Robotic writing trace synthesis and its application in the study of signature line quality. Journal of Forensic Document Examination, 119 - 141.
Bulacu, M. L., & Schomaker, L. R. B. (2005). Text-pose estimation in 3D using edge-direction distributions. In M. Kamel, & A. Campilho (Eds.), Proceedings of the International Conference on Image Analysis and Recognition (ICIAR 2005) (Vol. LNCS 3656, pp. 625-634). (Lecture Notes in Computer Science; Vol. 3656). BERLIN: Springer.

2004

Franke, K., Guyon, I., Schomaker, L., & Vuurpijl, L. (2004). The WANDAML Markup Language for Digital Document Annotation. 563-568. IWFHR 2004, Tokyo, Japan. https://doi.org/10.1109/IWFHR.2004.104
Schomaker, L., & Bulacu, M. (2004). Automatic writer identification using connected-component contours and edge-based features of uppercase western script. Ieee transactions on pattern analysis and machine intelligence, 26(6), 787-798.
Schomaker, L. (2004). Anticipation in cybernetic systems: A case against mindless anti-representationalism. In 2004 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN & CYBERNETICS, VOLS 1-7 (pp. 2037-2045). (IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS, CONFERENCE PROCEEDINGS). NEW YORK: IEEE (The Institute of Electrical and Electronics Engineers).
Ekker, R., van der Werf, ECD., & Schomaker, LRB. (2004). Dedicated TD-learning for Stronger Gameplay: applications to Go. 46-52.
Wang, F., Vuurpijl, L., & Schomaker, L. (2004). SUPPORT VECTOR MACHINES FOR THE CLASSIFICATION OF WESTERN HANDWRITTEN CAPITALS. In EPRINTS-BOOK-TITLE s.n..
Ezaki, N., Bulacu, M., & Schomaker, L. (2004). Text Detection from Natural Scene Images: Towards a System for Visually Impaired Persons. In Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004 (pp. 683-686). (Pattern Recognition (ICPR), 2004 17th International Conference on). IEEE (The Institute of Electrical and Electronics Engineers). https://doi.org/10.1109/ICPR.2004.1334351
Vuurpijl, L., Niels, R., Van Erp, M., Schomaker, L., & Ratzlaff, E. (2004). Verifying the UNIPEN devset. In Proceedings of the 9th International Workshop on Frontiers in Handwriting Recognition, 2004: IWFHR-9 2004 (pp. 586-591). (Proceedings - International Workshop on Frontiers in Handwriting Recognition, IWFHR). IEEE (The Institute of Electrical and Electronics Engineers). https://doi.org/10.1109/IWFHR.2004.109

2003

Vuurpijl, L., Schomaker, L. R. B., & van Erp, M. (2003). Architectures for detecting and solving conflicts: two-stage classification and support vector classifiers. International Journal on Document Analysis and Recognition, 4, 213 - 223.
Fehrmann, R., & Schomaker, L. (2003). Learning an approximate map of the environment by unsupervised bimodal landmark exploration. 275-282.
Schomaker, L. R. B. (2003). Patronen en symbolen; een wereld door het oog van de machine. MUON, 87, 8 - 13.
Franke, K., & Schomaker, L. (2003). Pen orientation characteristics of on-line handwritten signatures. 224-227.
Chhabra, A. K., Schomaker, L. R. B., & Kim, J. H. (2003). Proceedings of the 7th Intern. conference on Document Analysis and Recognition. Piscataway: IEEE (The Institute of Electrical and Electronics Engineers).
Schomaker, L., Bulacu, M., & van Erp, M. (2003). Sparse-parametric writer identification using heterogeneous feature groups. In 2003 INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, VOL 1, PROCEEDINGS (pp. 545-548). (IEEE International Conference on Image Processing (ICIP)). NEW YORK: IEEE (The Institute of Electrical and Electronics Engineers).
Bulacu, M., Schomaker, L., & Vuurpijl, L. (2003). Writer identification using edge-based directional features. In SEVENTH INTERNATIONAL CONFERENCE ON DOCUMENT ANALYSIS AND RECOGNITION, VOLS I AND II, PROCEEDINGS (pp. 937-941). LOS ALAMITOS: IEEE (The Institute of Electrical and Electronics Engineers).
Bulacu, M., & Schomaker, L. (2003). Writer style from oriented edge fragments. In N. Petkov, & MA. Westenberg (Eds.), COMPUTER ANALYSIS OF IMAGES AND PATTERNS, PROCEEDINGS (pp. 460-469). (LECTURE NOTES IN COMPUTER SCIENCE; Vol. 2756). BERLIN: Springer.

2002

Van Erp, M., Vuurpijl, L., & Schomaker, L. (2002). An overview and comparison of voting methods for pattern recognition. 195-200. Paper presented at IWFHR 2002, Niagara on the lake, Canada. https://doi.org/10.1109/IWFHR.2002.1030908
Schomaker, L. (2002). Patronen en symbolen: een wereld door het oog van de machine. s.n.
Schomaker, L. (2002). Patterns and symbols: a world through the eye of the machine. s.n.
Vuurpijl, L., Van Den Broek, E., & Schomaker, L. (2002). Vind (x): Using the user through cooperative annotation. 221-226. https://doi.org/10.1109/IWFHR.2002.1030913

2001

Schomaker, L. (2001). Image Search and Annotation: From Lab to Web. In Document Electronique: Methodes, demarches et techniques cognitives (pp. 373-375). Paris: Europia Productions.

2000

Simons, J., Arampatzis, A., Wondergem, B., Schomaker, L., van Bommel, P., Hoenkamp, E., ... Koster, C. (2000). PROFILE: A Multi-disciplinary approach to information discovery. Technical Report CSI-R0001. Nijmegen: Radboud University Nijmegen.
Benoit, C., Martin, J. C., Pelachaud, C., Schomaker, L., & Suhm, B. (2000). Audio-visual and multimodal speech-based systems. In D. Gibbon, I. Mertens, & R. Moore (Eds.), Handbook of multimodal and spoken dialogue systems: Resources, terminology and product evaluation (pp. 102-203). Dordrecht: Kluwer.
Schomaker, L., Vuurpijl, L., & Schomaker, L. (2000). Forensic writer identification: a benchmark data set and a comparison of two systems. [Nijmegen: NICI (NIjmegen Institute of Cognitive Information), Katholieke Universiteit Nijmegen.
Schomaker, L. R. B., Vuurpijl, L., International Workshop on Frontiers in Handwriting Recognition, & Nijmeegs Instituut voor Cognitie-Onderzoek en Informatietechnologie (2000). Proceedings 7th International Workshop on frontiers in handwriting recognition : September 11-13, 2000, Amsterdam, The Netherlands. Nijmegen: International Unipen Foundation.
Schomaker, L., Mangalagiu, D., Vuurpijl, L., & Weinfeld, M. (2000). Two tree-formation methods for fast pattern search using nearest-neighbour and nearest-centroid matching. In L. Schomaker, & L. Vuurpijl (Eds.), Proceedings of the Seventh International Workshop on Frontiers in Handwriting Recognition (7th IWFHR) (pp. 261-270). Nijmegen: International Unipen Foundation.
Vuurpijl, L., & Schomaker, L. (2000). TWO-STAGE CHARACTER CLASSIFICATION: A COMBINED APPROACH OF CLUSTERING AND SUPPORT VECTOR CLASSIFIERS. In Proceedings of the Seventh International Workshop Nijmegen: International Unipen Foundation.
van Erp, M., & Schomaker, L. (2000). Variants of the Borda count method for combining ranked classifier hypotheses. In L. Schomaker, & L. Vuurpijl (Eds.), Proceedings 7th International Workshop on frontiers in handwriting recognition (7th IWFHR): September 11-13, 2000, Amsterdam, The Netherlands (pp. 443-452). Nijmegen: International Unipen Foundation.

1999

Schomaker, L., & Segers, E. (1999). Finding features used in the human reading of cursive handwriting. International Journal on Document Analysis and Recognition, 2(1), 13-18. https://doi.org/10.1007/s100320050031
Schomaker, L., Vuurpijl, L., & De Leau, E. (1999). New use for the pen: Outline-based image queries. 293-296. Proceedings of the Fifth International Conference on Document Analysis and Recognition. ICDAR '99 (Cat. No.PR00318), Bangalore, India, United Kingdom. https://doi.org/10.1109/ICDAR.1999.791782
Plamondon, R., Lopresti, D., Schomaker, L., & Srihari, R. (1999). On-line handwriting recognition. In Encyclopedia of Electrical & Electronics Engineering (pp. 123-146). New York: Wiley.
Hoenkamp, E., Stegeman, O., & Schomaker, L. (1999). Supporting content retrieval from WWW via 'basic level categories'. In Proceedings of the 22rd International Conference on Research and Development in Information Retrieval (3 ed., Vol. 33, pp. 311-312). ACM Press Digital Library.
Schomaker, L., de Leau, E., & Vuurpijl, L. (1999). Using Pen-Based Outlines for Object-Based Annotation and Image-Based Queries. In D. Huijsmans, & A. Smeulders (Eds.), Visual Information and Information Systems (pp. 585-592). (Lecture Notes in Computer Science; Vol. 1614). Springer. https://doi.org/10.1007/3-540-48762-X_72

1998

Schomaker, L. (1998). A method for the determination of features used in human reading of cursive handwriting. In Proceedings of IWFHR'98, 12-14 August, Taejon, Korea (pp. 157-168). Taejon.
Schomaker, L., Hoenkamp, E., & Mayberry, M. (1998). Towards collaborative agents for automatic on-line handwriting recognition. In Proceedings of the Third European Workshop on Handwriting Analysis and Recognition (pp. 1-6). (Digest Number ; Vol. 440, No. -). London: The Institution of Electrical Engineers, IEE, London.
Schomaker, L. (1998). From handwriting analysis to pen-computer applications. Electronics & Communication Engineering Journal, 10(3), 93-102. https://doi.org/10.1049/ecej:19980302
Vuurpijl, L., & Schomaker, L. (1998). A framework for using multiple classifiers in a multiple-agent architecture. 8-8. https://doi.org/10.1049/ic:19980682
Schomaker, L. (1998). An overview of pen computing: Four perspectives. 1. https://doi.org/10.1049/ic:19980675
Schomaker, L. (1998). Entre écrire des formes sur une ardoise et le traitement d'information utilisable.. 9-13. Paper presented at Actes du 1er Colloque International Francophone sur l'Écrit et le document, Quebec, Canada.

1997

Schomaker, L., Hartung, K., Muench, S., Le Goff, B., MacLaverty, R., Nijtmans, J., ... Defee, I. (1997). Final Report: Findings, Demonstrators and other Results, Report of Esprit Project 8579/MIAMI. Nijmegen: Radboud University Nijmegen.
Vuurpijl, L., & Schomaker, L. (1997). Finding structure in diversity: a hierarchical clustering methodfor the categorization of allographs in handwriting. In Proceedings of the Fourth International Conference on Document Analysis and Recognition, 1997 (pp. 387-393). (Proceedings of the Fourth International Conference on Document Analysis and Recognition; Vol. 1). IEEE (The Institute of Electrical and Electronics Engineers). https://doi.org/10.1109/ICDAR.1997.619876
Mackowiak, J., Schomaker, L., & Vuurpijl, L. (1997). Semi-automatic determination of allograph duration and position in on-line handwriting words based on the expected number of strokes. In A. Downton, & S. Impedovo (Eds.), Progress in Handwriting Recognition (pp. 69-74)

1996

Vuurpijl, L., & Schomaker, L. (1996). Coarse writing-style clustering based on simple stroke-related features. In Proceedings of the 5th International Workshop on Frontiers in Handwriting Recognition (pp. 29-34). Colchester.
Schomaker, L., & van Galen, GP. (1996). Computer models of handwriting. In A. Dijkstra, & K. de Smedt (Eds.), Computational Psycholinguistics: AI and connectionist models of human language processing (pp. 386-420). London: Taylor & Francis Group.

1995

Schomaker, L. (1995). A report of the ESPRIT Project 8579 MIAMI. [S.n.].
Schomaker, L. (1995). A taxonomy of Multimodal Interaction in the Human Information Processing System. [S.l: s.n.

1994

Schomaker, L., Abbink, G., & Selen, S. (1994). Writer and writing-style classification in the recognition of online handwriting. Abstract from IEE European Workshop on, Brussels, Belgium.
Teulings, H. L., & Schomaker, L. R. (1994). Invariant Handwriting Features Useful in Cursive-Script Recognition. In S. Impedovo (Ed.), Fundamentals in Handwriting Recognition: Part 3 (Vol. 124, pp. 179-198). (NATO ASI Series / Series F: Computer and Systems Sciences; Vol. 124). Springer. https://doi.org/10.1007/978-3-642-78646-4_9
Vos, P. G., van Dijk, A., & Schomaker, L. (1994). Melodic cues for metre. Perception, 23(8), 965-976.
Helsper, E. L., Schomaker, L. R., & Teulings, H-L. (1994). Recognizing historic handwriting. In F. Bocchi, & P. Denley (Eds.), Storia & multimedia: atti del settimo Congresso internazionale: Proceedings of the seventh international congress (Association for history & computing) Grafis Edizione.
Guyon, I., Schomaker, L., Plamondon, R., Liberman, M., & Janet, S. (1994). UNIPEN project of on-line data exchange and recognizer benchmarks. 29-33. https://doi.org/10.1109/ICPR.1994.576870
Schomaker, L. (1994). User-interface aspects in recognizing connected-cursive handwriting.

1993

Schomaker, L. R. B., Helsper, E. H., Teulings, H. L., & Abbink, G. H. (1993). Adaptive recognition of online, cursive handwriting. In Proceedings of the Sixth International Conference on Handwriting and Drawing. (pp. 19-21). Paris: Telecom France.
MEULENBROEK, RGJ., ROSENBAUM, DA., THOMASSEN, AJWM., SCHOMAKER, LRB., & Schomaker, L. (1993). LIMB-SEGMENT SELECTION IN DRAWING BEHAVIOR. Quarterly journal of experimental psychology section a-Human experimental psychology, 46(2), 273-299.
Meulenbroek, R. G., Rosenbaum, D. A., Thomassen, A. J. W. M., & Schomaker, L. R. (1993). Limb-segment selection in drawing behaviour. Quarterly journal of experimental psychology section a-Human experimental psychology, 46(2), 273-99.
Teulings, H. L., & Schomaker, L. R. (1993). Invariant properties between stroke features in handwriting. Acta Psychologica, 82(1-3), 69-88.
van Galen, G. P., Portier, S. J., Smits-Engelsman, B. C., & Schomaker, L. R. (1993). Neuromotor noise and poor handwriting in children. Acta Psychologica, 82(1-3), 161-178.
SCHOMAKER, L. (1993). USING STROKE-BASED OR CHARACTER-BASED SELF-ORGANIZING MAPS IN THE RECOGNITION OF ONLINE, CONNECTED CURSIVE SCRIPT. Pattern recognition, 26(3), 443-450.
Abbink, G., Teulings, H-L., & Schomaker, L. (1993). Description of on-line script using Hollerbach's generation model. In Proceedings of the Third International Workshop on Frontiers in Handwriting Recognition (IWFHR-III) (pp. 25-27). Buffalo.
Helsper, E. L., Schomaker, L., Teulings, H-L., & Abbink, G. (1993). Feature description of optically scanned handwritten words. I. In C. Faure (Ed.), Proceedings of the Sixth International IGS conference on handwriting and drawing (pp. 270-272). Paris: Telecom France.
Helsper, E. L., & Schomaker, L. (1993). Off-line and On-line Handwriting Recognition: The Role of Pen Movement in Machine Reading. In M. Thaller (Ed.), Halbgraue Reihe zur Historischen Fachinformatik (pp. 39-51). (Serie A: Historische Quellenkunden; Vol. 18). Göttingen: Max-Planck-Institut für Gescichte.
Helsper, E. L., & Schomaker, L. (1993). Tools for the recognition of handwritten historical documents. History and Computing, 5(2), 88-93.

1992

Schomaker, L. (1992). A NEURAL OSCILLATOR-NETWORK MODEL OF TEMPORAL PATTERN GENERATION. Human Movement Science, 11(1-2), 181-192.
VANGALEN, GP., SCHOMAKER, LRB., & Schomaker, L. (1992). FITTS LAW AS A LOW-PASS FILTER EFFECT OF MUSCLE-STIFFNESS. Human Movement Science, 11(1-2), 11-21.

1991

Teulings, H-L., & Schomaker, L. (1991). Invariant properties of handwriting motor programs to be employed in automatic cursive-script recognition. In G. Stelmach (Ed.), Proceedings of the Fifth Handwriting Conference of the IGS: Motor Control of Handwriting (pp. 21-23). Tempe, AZ: Arizona State University.
Schomaker, L. (1991). Simulation and recognition of handwriting movements: a vertical approach to modeling human motor behavior. Nijmegen: NICI (NIjmegen Institute of Cognitive Information), Katholieke Universiteit Nijmegen.
Schomaker, L., & Teulings, H-L. (1991). Stroke- versus Character-based Recognition of On-line, Connected Cursive Script. In Proceedings of the 2nd International Workshop on Frontiers in Handwriting Recognition (IWFHR-2) (pp. 265-277). Chateau de Bonas, France.
Schomaker, L. (1991). Un-supervised learning of prototype allographs in cursive script recognition using invariant handwriting features. In Proceedings of the 2nd International Workshop on Frontiers in Handwriting Recognition (IWFHR-2). (pp. 45-55). Chateau de Bonas, France.

1990

Van Galen, G. P., Van Doorn, R. R., & Schomaker, L. R. (1990). Effects of motor programming on the power spectral density function of finger and wrist movements. Journal of Experimental Psychology : Human Perception and Performance, 16(4), 755-765.
Schomaker, L. R. B., & Plamondon, R. (1990). The relation between Pen Force and Pen-Point kinematics in handwriting. Biological Cybernetics, 63(4), 277-289.
Schomaker, L. (1990). A Handwriting Recognition System based on the Properties and Architectures of the Human Motor System. In Proceedings of the International Workshop on Frontiers in Handwriting Recognition (IWFHR) (pp. 195-211). Montreal: CENPARMI Concordia.
Teulings, H-L., Schomaker, L., Gerritsen, J., Drexler, H., & Albers, M. (1990). An on-line handwriting-recognition system based on unreliable modules. In R. Plamondon, & G. Leedham (Eds.), Computer Processing of Handwriting (pp. 167-185). Singapore: World Scientific Publishing.

1989

Schomaker, L., Thomassen, A. J. W. M., & Teulings, H-L. (1989). A computational model of cursive handwriting. In Computer Recognition and Human Production of Handwriting (pp. 153-177). World Scientific Publishing.

1988

Teulings, H-L., Schomaker, L., & Maarse, F. J. (1988). Automatic handwriting recognition and the keyboardless personal computer. In Computers in psychology: Methods, instrumentation, and psychodiagnostics (pp. 62-66). Amsterdam: Swets & Zeitlinger.
Maarse, F. J., Schomaker, L., & Teulings, H-L. (1988). Automatic identification of writers. In G. C. van der Veer, & G. Mulder (Eds.), Human-Computer Interaction: Psychonomic Aspects (pp. 353-360). Springer.
Thomassen, A. J. W. M., Teulings, H-L., & Schomaker, L. (1988). Real-time processing of cursive writing and sketched graphics. In Human-Computer Interaction: Psychonomic Aspects (pp. 334-352). Springer.
Schomaker, L. (1988). Robotica en menselijke motoriek. In Psychonomische Publikaties: Menselijke Motoriek (pp. 117). Amsterdam: Swets & Zeitlinger.
Thomassen, A. J. W. M., Teulings, H-L., Schomaker, L., Morasso, P., & Kennedy, J. (1988). Towards the implementation of cursive-script understanding in an online handwriting-recognition system. In D. G. XIII (Ed.), ESPRIT '88: Putting the technology to use (pp. 628-639). European Commission.

1987

Schomaker, L., Thomassen, A. J. W. M., & Teulings, H-L. (1987). A computational model of cursive handwriting. In R. Plamondon, C. Y. Suen, & J. G. Deschenes (Eds.), Proceedings of the Third International Symposium on Handwriting and Computer Applications (pp. 5-7). Montreal, Ecole Polytechnique.
Teulings, H-L., Schomaker, L., Thomassen, A. J. W. M., & Morasso, P. (1987). Experimental protocol for cursive script acquisition: The use of motor information for the automatic recognition of cursive script. European Commission.
Teulings, H-L., Schomaker, L., Thomassen, A. J. W. M., & Morasso, P. (1987). Handwriting-analysis system. In Proceedings of the Third International Symposium on Handwriting and Computer Applications (pp. 181-183)
Schomaker, L. R. B. (1987). Robotica en menselijke motoriek. Nijmegen: Katholieke Universiteit, Psychologisch Laboratorium.

1986

Thomassen, A. J. W. M., & Schomaker, L. (1986). Between-letter context effects in handwriting trajectories. In H. S. R. Kao, G. P. van Galen, & R. Hoosain (Eds.), Graphonomics: Contemporary research in handwriting (pp. 253-272). North-Holland Publishing Company.
Schomaker, L., & Thomassen, A. J. W. M. (1986). On the use and limitations of averaging handwriting signals. In H. S. R. Kao, G. P. van Galen, & R. Hoosain (Eds.), Graphonomics: Contemporary research in handwriting (pp. 225-238). North-Holland Publishing Company.
Maarse, F. J., Schomaker, L., & Thomassen, A. J. W. M. (1986). The influence of changes in the effector coordinate systems on handwriting movements. In H. S. R. Kao, G. P. van Galen, & R. Hoosain (Eds.), Graphonomics: Contemporary research in handwriting (pp. 33-46). North-Holland Publishing Company.

1984

van Boxtel, A., Goudswaard, P., & Schomaker, L. R. (1984). Amplitude and bandwidth of the frontalis surface EMG: effects of electrode parameters. Psychophysiology, 21(6), 699-707.
VINGERHOETS, AJJM., SCHOMAKER, LRB., & Schomaker, L. (1984). FAINTING AS A STRESS RESPONSE - PSYCHOLOGICAL AND PHYSIOLOGICAL-ASPECTS. Gedrag : Tijdschrift voor psychologie, 12(1-2), 46-59.
van Boxtel, A., & Schomaker, L. R. (1984). Influence of motor unit firing statistics on the median frequency of the EMG power spectrum. European journal of applied physiology and occupational physiology, 52(2), 207-213.

1983

van Boxtel, A., & Schomaker, L. R. (1983). Motor unit firing rate during static contraction indicated by the surface EMG power spectrum. Ieee transactions on biomedical engineering, 30(9), 601-9.
VANBOXTEL, A., SCHOMAKER, LRB., GOUDSWAARD, P., VANDERMOLEN, GM., & Schomaker, L. (1983). POWER SPECTRA OF SURFACE EMG OF FACIAL AND JAW-ELEVATOR MUSCLES IN RELATION TO MOTOR UNIT FIRING RATE AND FATIGUE. Electroencephalography and clinical Neurophysiology, 56(3), 191-191.
VANBOXTEL, A., GOUDSWAARD, P., SCHOMAKER, LRB., & Schomaker, L. (1983). RECORDING METHODS FOR THE FRONTALIS SURFACE EMG. Psychophysiology, 20(4), 475-475.

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BOELHOUWER, AJW., GREGORIC, M., VANDENBOSCH, WEJ., SCHOMAKER, LRB., BRUNIA, CHM., & Schomaker, L. (1982). HABITUATION OF THE HUMAN BLINK REFLEX - THE EFFECT OF STIMULUS FREQUENCY AND THE STATE OF AROUSAL. Physiological psychology, 10(3), 325-330.
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