Saeed Reza Kheradpisheh, Ph.D.

Affiliations: 
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 
Area:
Spiking Neural Networks, Deep Learning
Google:
"Saeed Kheradpisheh"
Mean distance: (not calculated yet)
 
BETA: Related publications

Publications

You can help our author matching system! If you notice any publications incorrectly attributed to this author, please sign in and mark matches as correct or incorrect.

Kheradpisheh SR, Masquelier T. (2020) Temporal Backpropagation for Spiking Neural Networks with One Spike per Neuron. International Journal of Neural Systems. 2050027
Ramezani F, Kheradpisheh SR, Thorpe SJ, et al. (2019) Object categorization in visual periphery is modulated by delayed foveal noise. Journal of Vision. 19: 1
Tavanaei A, Ghodrati M, Kheradpisheh SR, et al. (2019) Deep learning in spiking neural networks. Neural Networks : the Official Journal of the International Neural Network Society. 111: 47-63
Masquelier T, Kheradpisheh SR. (2018) Optimal Localist and Distributed Coding of Spatiotemporal Spike Patterns Through STDP and Coincidence Detection. Frontiers in Computational Neuroscience. 12: 74
Mozafari M, Kheradpisheh SR, Masquelier T, et al. (2018) First-Spike-Based Visual Categorization Using Reward-Modulated STDP. Ieee Transactions On Neural Networks and Learning Systems
Kheradpisheh SR, Ganjtabesh M, Thorpe SJ, et al. (2017) STDP-based spiking deep convolutional neural networks for object recognition. Neural Networks : the Official Journal of the International Neural Network Society. 99: 56-67
Ashtiani MN, Kheradpisheh SR, Masquelier T, et al. (2017) Object Categorization in Finer Levels Relies More on Higher Spatial Frequencies and Takes Longer. Frontiers in Psychology. 8: 1261
Kheradpisheh SR, Ghodrati M, Ganjtabesh M, et al. (2016) Humans and Deep Networks Largely Agree on Which Kinds of Variation Make Object Recognition Harder. Frontiers in Computational Neuroscience. 10: 92
Kheradpisheh SR, Ghodrati M, Ganjtabesh M, et al. (2016) Deep Networks Can Resemble Human Feed-forward Vision in Invariant Object Recognition. Scientific Reports. 6: 32672
Kheradpisheh SR, Nowzari-Dalini A, Ebrahimpour R, et al. (2014) An evidence-based combining classifier for brain signal analysis. Plos One. 9: e84341
See more...