Publication

Comparative study between deep learning and bag of visual words for wild-animal recognition

Okafor, E., Pawara, P., Karaaba, M., Surinta, O., Codreanu, V., Schomaker, L. & Wiering, M., 9-Feb-2017, 2016 IEEE Symposium Series on Computational Intelligence, SSCI 2016. Institute of Electrical and Electronics Engineers Inc., (2016 IEEE Symposium Series on Computational Intelligence, SSCI 2016).

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

Copy link to clipboard

Documents

  • Comparative Study Between Deep Learning and Bag of Visual Words for Wild-Animal Recognition

    Final publisher's version, 653 KB, PDF-document

    Request copy

Links

DOI

© 2016 IEEE.Most research in image classification has focused on applications such as face, object, scene and character recognition. This paper examines a comparative study between deep convolutional neural networks (CNNs) and bag of visual words (BOW) variants for recognizing animals. We developed two variants of the bag of visual words (BOW and HOG-BOW) and examine the use of gray and color information as well as different spatial pooling approaches. We combined the final feature vectors extracted from these BOW variants with a regularized L2 support vector machine (L2-SVM) to distinguish between classes within our datasets. We modified existing deep CNN architectures: AlexNet and GoogleNet, by reducing the number of neurons in each layer of the fully connected layers and last inception layer for both scratch and pre-trained versions. Finally, we compared the existing CNN methods, our modified CNN architectures and the proposed BOW variants on our novel wild-animal dataset (Wild-Anim). The results show that the CNN methods significantly outperform the BOW techniques.
Original languageEnglish
Title of host publication2016 IEEE Symposium Series on Computational Intelligence, SSCI 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Print)9781509042401
Publication statusPublished - 9-Feb-2017

Publication series

Name2016 IEEE Symposium Series on Computational Intelligence, SSCI 2016
Related Datasets
  1. Wild-Anim Dataset

    Okafor, E. (Creator), Schomaker, L. (Creator), Wiering, M. (Creator), University of Groningen, 25-Feb-2019

    Dataset

View all (1) »

View graph of relations

ID: 42732679