| Converting static image datasets to spiking neuromorphic datasets using saccades G Orchard, A Jayawant, GK Cohen, N Thakor Frontiers in neuroscience 9, 437, 2015 | 147 | 2015 |
| HFirst: A Temporal Approach to Object Recognition G Orchard, C Meyer, R Etienne-Cummings, C Posch, N Thakor, ... Pattern Analysis and Machine Intelligence, IEEE Transactions on 37 (10 …, 2015 | 133 | 2015 |
| Hots: a hierarchy of event-based time-surfaces for pattern recognition X Lagorce, G Orchard, F Galluppi, BE Shi, RB Benosman IEEE transactions on pattern analysis and machine intelligence 39 (7), 1346-1359, 2016 | 131 | 2016 |
| Slayer: Spike layer error reassignment in time SB Shrestha, G Orchard Advances in Neural Information Processing Systems, 1412-1421, 2018 | 97 | 2018 |
| Event-based vision: A survey G Gallego, T Delbruck, G Orchard, C Bartolozzi, B Taba, A Censi, ... arXiv preprint arXiv:1904.08405, 2019 | 82 | 2019 |
| Optimization methods for spiking neurons and networks A Russell, G Orchard, Y Dong, Ş Mihalaş, E Niebur, J Tapson, ... IEEE transactions on neural networks 21 (12), 1950-1962, 2010 | 48 | 2010 |
| Skimming digits: neuromorphic classification of spike-encoded images GK Cohen, G Orchard, SH Leng, J Tapson, RB Benosman, A Van Schaik Frontiers in neuroscience 10, 184, 2016 | 37 | 2016 |
| Fast Neuromimetic Object Recognition Using FPGA Outperforms GPU Implementations G Orchard, JG Martin, RJ Vogelstein, R Etienne-Cummings Neural Networks and Learning Systems, IEEE Transactions on 24 (8), 1239-1252, 2013 | 35 | 2013 |
| Bioinspired Visual Motion Estimation G Orchard, R Etienne-Cummings Proceedings of the IEEE 102 (10), 1520 - 1536, 2014 | 33 | 2014 |
| Benchmarking neuromorphic vision: lessons learnt from computer vision C Tan, S Lallee, G Orchard Frontiers in neuroscience 9, 374, 2015 | 31 | 2015 |
| Configuring of spiking central pattern generator networks for bipedal walking using genetic algorthms A Russell, G Orchard, R Etienne-Cummings 2007 IEEE International Symposium on Circuits and Systems, 1525-1528, 2007 | 30 | 2007 |
| Real-time object recognition and orientation estimation using an event-based camera and CNN R Ghosh, A Mishra, G Orchard, NV Thakor 2014 IEEE Biomedical Circuits and Systems Conference (BioCAS) Proceedings …, 2014 | 25 | 2014 |
| Dart: distribution aware retinal transform for event-based cameras B Ramesh, H Yang, GM Orchard, NA Le Thi, S Zhang, C Xiang IEEE transactions on pattern analysis and machine intelligence, 2019 | 24 | 2019 |
| A noise filtering algorithm for event-based asynchronous change detection image sensors on truenorth and its implementation on truenorth V Padala, A Basu, G Orchard Frontiers in neuroscience 12, 118, 2018 | 24 | 2018 |
| Neuromorphic event-based 3d pose estimation D Reverter Valeiras, G Orchard, SH Ieng, RB Benosman Frontiers in neuroscience 9, 522, 2016 | 24 | 2016 |
| Real time compressive sensing video reconstruction in hardware G Orchard, J Zhang, Y Suo, M Dao, DT Nguyen, S Chin, C Posch, TD Tran, ... IEEE Journal on Emerging and Selected Topics in Circuits and Systems 2 (3 …, 2012 | 22 | 2012 |
| Real-time event-driven spiking neural network object recognition on the SpiNNaker platform G Orchard, X Lagorce, C Posch, SB Furber, R Benosman, F Galluppi 2015 IEEE International Symposium on Circuits and Systems (ISCAS), 2413-2416, 2015 | 21 | 2015 |
| Spiking optical flow for event-based sensors using IBM's truenorth neurosynaptic system G Haessig, A Cassidy, R Alvarez, R Benosman, G Orchard IEEE transactions on biomedical circuits and systems 12 (4), 860-870, 2018 | 19 | 2018 |
| Event-based stereo depth estimation using belief propagation Z Xie, S Chen, G Orchard Frontiers in neuroscience 11, 535, 2017 | 18 | 2017 |
| Evaluating noise filtering for event-based asynchronous change detection image sensors D Czech, G Orchard 2016 6th IEEE International Conference on Biomedical Robotics and …, 2016 | 18 | 2016 |
Ralph Etienne-CummingsJohns Hopkins UniversityVerified email at jhu.edu
