My research interests are in computer vision, deep (machine) learning and computational models of biological vision. In particular, I am interested in
"Self-Supervised Learning of 3D Human Pose using Multi-view Geometry"
Muhammed Kocabas, Salih Karagoz, Emre Akbas
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019.
pdf | link | bibtex | code
"MultiPoseNet: Fast Multi-Person Pose Estimation using Pose Residual Network"
Muhammed Kocabas, Salih Karagoz, Emre Akbas
European Conference on Computer Vision (ECCV), 2018.
pdf | link | bibtex | code | implementation by others: link
"Localization Recall Precision (LRP): A New Performance Metric for Object Detection"
Kemal Oksuz, Baris Can Cam, Emre Akbas, Sinan Kalkan
European Conference on Computer Vision (ECCV), 2018.
pdf | link | bibtex | code
"Object detection through search with a foveated visual system"
Emre Akbas, Miguel P. Eckstein
PLOS Computational Biology, 2017.
pdf | link | bibtex | code
★ This work was selected as the cover of the October 2017 issue.
"Humans but not deep neural networks miss giant targets in scenes"
Miguel P. Eckstein, Kathryn Koehler, Lauren Welbourne, Emre Akbas
Current Biology, 2017.
pdf | link | bibtex
★ This work has appeared in UCSB press release, EurekAlert, ScienceDaily and The New York Times.
"Could we create a training set for image captioning using automatic translation?" (in Turkish)
Nermin Samet, Samet Hicsonmez, Pinar Duygulu, Emre Akbas
25th Signal Processing and Communications Applications Conference (SIU), 2017.
link
"Decoding cognitive states using the bag of words model on fMRI time series"
Güneş Sucu, Emre Akbaş, İlke Öztekin, Eda Mızrak, Fatoş Yarman Vural
Intl. Workshop on Machine Learning for Understanding the Brain, in conj. with 24th Signal Processing and Communication Application Conference (SIU), 2016.
pdf | link | bibtex
"Optimal and human eye movements to clustered low value cues to increase decision rewards during search"
Miguel P. Eckstein, Wade Schoonveld, Sheng Zhang, Stephen C. Mack, Emre Akbas
Vision Research, 2015.
pdf | link | bibtex
"Low-level hierarchical segmentation statistics of natural images"
Emre Akbas, Narendra Ahuja
IEEE Transactions on Pattern Analysis Machine Intelligence (TPAMI), 2014.
pdf | link | bibtex
"The Front End for Mammalian Vision: a Detailed Model and Its Implications for Machine Learning"
Emre Akbas, Aseem Wadha, Miguel Eckstein and Upamanyu Madhow
52nd Annual Allerton Conference on Communication, Control, and Computing, University of Illinois at Urbana-Champaign, 2014.
pdf | link | bibtex
"Pedestrian recognition with a learned metric"
Mert Dikmen, Emre Akbas, Thomas S. Huang, Narendra Ahuja
Asian Conference in Computer Vision (ACCV), 2010.
pdf | link | bibtex
"Low-level segmentation based scene classification"
Emre Akbas, Narendra Ahuja
International Conference on Pattern Recognition (ICPR), 2010.
pdf | link | bibtex
"From ramp discontinuities to segmentation tree"
Emre Akbas, Narendra Ahuja
Asian Conference in Computer Vision (ACCV), 2009.
pdf | link | bibtex
"Automatic Image Annotation by Ensemble of Visual Descriptors"
Emre Akbas, Fatos T. Yarman Vural
Workshop on Semantic Learning Applications in Multimedia, Conference on Computer Vision and Pattern Recognition (CVPRW), 2007.
pdf | link | bibtex
"A Hierarchical Classification System Based on Adaptive Resonance Theory"
Mutlu Uysal, Emre Akbas, Fatos T. Yarman Vural
International Conference on Image Processing (ICIP), 2006.
pdf | link | bibtex
"Design of a Feature Set for Face Recognition Problem"
Emre Akbas, Fatos T. Yarman Vural
International Symposium on Computer and Information Sciences (ISCIS), 2006.
pdf | link | bibtex
"A Comparison of Feature Spaces for Face Recognition Problem" (in Turkish)
Gulsah T. Ozyer, Emre Akbas, Fatos T. Yarman Vural
IEEE Conference on Signal Processing and Communications Applications (SIU), 2006.
pdf | link | bibtex
"A Comparison of the Performances of Fuzzy ARTMAP and AdaBoost Classification Algorithms in Image Retrieval" (in Turkish)
Emre Akbas, Ozge Ozcanli, Fatos T. Yarman Vural
IEEE Conference on Signal Processing and Communications Applications (SIU), 2005.
pdf | link | bibtex