Friedrich Melchert

Publications
  1. A Low-Cost 3-D Printed Smartphone Add-on Spectrometer for Diagnosis of Crop Diseases in Field

    Owomugisha, G., Mugagga, P. K. B., Melchert, F., Mwebaze, E., Quinn, J. A. & Biehl, M., Jun-2020, Proceedings of the 3rd ACM SIGCAS Conference on Computing and Sustainable Societies. New York, NY, USA: Association for Computing Machinery, p. 331–332

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

  2. Data dependent evaluation of dissimilarities in nearest prototype vector quantizers regarding their discriminating abilities

    Kaden, M., Nebel, D., Melchert, F., Backhaus, A., Seiffert, U. & Villmann, T., 31-Aug-2017, 12th International Workshop on Self-Organizing Maps and Learning Vector Quantization, Clustering and Data Visualization, WSOM 2017 - Proceedings. Lamirel, J-C., Olteanu, M. & Cottrell, M. (eds.). Institute of Electrical and Electronics Engineers Inc., p. 1-7 8 p. 8020030. (12th International Workshop on Self-Organizing Maps and Learning Vector Quantization, Clustering and Data Visualization, WSOM 2017 - Proceedings).

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

  3. Adaptive basis functions for prototype-based classification of functional data

    Melchert, F., Bani, G., Seiffert, U. & Biehl, M., 13-Jul-2019, In : Neural Computing and Applications. 11 p.

    Research output: Contribution to journalArticleAcademicpeer-review

  4. Learning vector quantization and relevances in complex coefficient space

    Straat, M., Kaden, M., Gay, M., Villmann, T., Lampe, A., Seiffert, U., Biehl, M. & Melchert, F., 9-Mar-2019, In : Neural Computing and Applications. 15 p.

    Research output: Contribution to journalArticleAcademicpeer-review

  5. Prototypes and matrix relevance learning in complex fourier space

    Straat, M., Kaden, M., Gay, M., Villmann, T., Lampe, A., Seiffert, U., Biehl, M. & Melchert, F., 31-Aug-2017, 12th International Workshop on Self-Organizing Maps and Learning Vector Quantization, Clustering and Data Visualization (WSOM). IEEEXplore, p. 1-6 6 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

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Activities
  1. Workshop on Self-Organizing Maps and Learning Vector Quantization, Clustering and Data Visualization

    Michael Biehl (Participant), Friedrich Melchert (Speaker), Michael LeKander (Speaker), Michiel Straat (Speaker)
    28-Jun-201730-Jun-2017

    Activity: Participating in or organising an eventParticipation in conferenceAcademic

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