Saeed Reza Kheradpisheh, Ph.D. - Publications

2013-2017 Computer Science university of tehran, Tehran, Tehran Province, Iran 
 2017-2018 School of Biological Sciences Institute for Research in Fundamental Sciences (IPM), Tehran, Tehran Province, Iran 
 2018-2020 Computer Science Shahid Beheshti University, Tehran, Tehran Province, Iran 
Spiking Neural Networks, Deep Learning

12/14 high-probability publications. We are testing a new system for linking publications to authors. You can help! If you notice any inaccuracies, please sign in and mark papers as correct or incorrect matches. If you identify any major omissions or other inaccuracies in the publication list, please let us know.

Year Citation  Score
2020 Kheradpisheh SR, Masquelier T. Temporal Backpropagation for Spiking Neural Networks with One Spike per Neuron. International Journal of Neural Systems. 2050027. PMID 32466691 DOI: 10.1142/S0129065720500276  0.717
2019 Ramezani F, Kheradpisheh SR, Thorpe SJ, Ghodrati M. Object categorization in visual periphery is modulated by delayed foveal noise. Journal of Vision. 19: 1. PMID 31369042 DOI: 10.1167/19.9.1  0.568
2019 Tavanaei A, Ghodrati M, Kheradpisheh SR, Masquelier T, Maida A. Deep learning in spiking neural networks. Neural Networks : the Official Journal of the International Neural Network Society. 111: 47-63. PMID 30682710 DOI: 10.1016/J.Neunet.2018.12.002  0.715
2018 Masquelier T, Kheradpisheh SR. Optimal Localist and Distributed Coding of Spatiotemporal Spike Patterns Through STDP and Coincidence Detection. Frontiers in Computational Neuroscience. 12: 74. PMID 30279653 DOI: 10.3389/Fncom.2018.00074  0.687
2018 Mozafari M, Kheradpisheh SR, Masquelier T, Nowzari-Dalini A, Ganjtabesh M. First-Spike-Based Visual Categorization Using Reward-Modulated STDP. Ieee Transactions On Neural Networks and Learning Systems. PMID 29993898 DOI: 10.1109/Tnnls.2018.2826721  0.735
2017 Kheradpisheh SR, Ganjtabesh M, Thorpe SJ, Masquelier T. STDP-based spiking deep convolutional neural networks for object recognition. Neural Networks : the Official Journal of the International Neural Network Society. 99: 56-67. PMID 29328958 DOI: 10.1016/J.Neunet.2017.12.005  0.752
2017 Ashtiani MN, Kheradpisheh SR, Masquelier T, Ganjtabesh M. Object Categorization in Finer Levels Relies More on Higher Spatial Frequencies and Takes Longer. Frontiers in Psychology. 8: 1261. PMID 28790954 DOI: 10.3389/Fpsyg.2017.01261  0.657
2017 Rubchinsky LL, Ahn S, Klijn W, Cumming B, Yates S, Karakasis V, Peyser A, Woodman M, Diaz-Pier S, Deraeve J, Vassena E, Alexander W, Beeman D, Kudela P, Boatman-Reich D, ... ... Kheradpisheh SR, et al. 26th Annual Computational Neuroscience Meeting (CNS*2017): Part 2 Bmc Neuroscience. 18. DOI: 10.1186/S12868-017-0371-2  0.645
2016 Kheradpisheh SR, Ghodrati M, Ganjtabesh M, Masquelier T. Humans and Deep Networks Largely Agree on Which Kinds of Variation Make Object Recognition Harder. Frontiers in Computational Neuroscience. 10: 92. PMID 27642281 DOI: 10.3389/Fncom.2016.00092  0.681
2016 Kheradpisheh SR, Ghodrati M, Ganjtabesh M, Masquelier T. Deep Networks Can Resemble Human Feed-forward Vision in Invariant Object Recognition. Scientific Reports. 6: 32672. PMID 27601096 DOI: 10.1038/Srep32672  0.687
2016 Kheradpisheh SR, Ganjtabesh M, Masquelier T. Bio-inspired unsupervised learning of visual features leads to robust invariant object recognition Neurocomputing. 205: 382-392. DOI: 10.1016/J.Neucom.2016.04.029  0.73
2014 Kheradpisheh SR, Sharifizadeh F, Nowzari-Dalini A, Ganjtabesh M, Ebrahimpour R. Mixture of feature specified experts Information Fusion. 20: 242-251. DOI: 10.1016/J.Inffus.2014.02.006  0.38
Low-probability matches (unlikely to be authored by this person)
2013 Kheradpisheh SR, Behjati-Ardakani F, Ebrahimpour R. Combining classifiers using nearest decision prototypes Applied Soft Computing. 13: 4570-4578. DOI: 10.1016/J.Asoc.2013.07.028  0.288
2014 Kheradpisheh SR, Nowzari-Dalini A, Ebrahimpour R, Ganjtabesh M. An evidence-based combining classifier for brain signal analysis. Plos One. 9: e84341. PMID 24392125 DOI: 10.1371/Journal.Pone.0084341  0.283
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