| A large contextual dataset for classification, detection and counting of cars with deep learning TN Mundhenk, G Konjevod, WA Sakla, K Boakye Computer Vision–ECCV 2016: 14th European Conference, Amsterdam, The …, 2016 | 289 | 2016 |
| Schizophrenia and the mirror system: an essay MA Arbib, TN Mundhenk Neuropsychologia 43 (2), 268-280, 2005 | 162 | 2005 |
| Improvements to context based self-supervised learning TN Mundhenk, D Ho, BY Chen Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018 | 127 | 2018 |
| Deep symbolic regression: Recovering mathematical expressions from data via risk-seeking policy gradients BK Petersen, ML Larma, TN Mundhenk, CP Santiago, SK Kim, JT Kim arXiv preprint arXiv:1912.04871, 2019 | 98 | 2019 |
| Truenorth ecosystem for brain-inspired computing: scalable systems, software, and applications J Sawada, F Akopyan, AS Cassidy, B Taba, MV Debole, P Datta, ... SC'16: Proceedings of the International Conference for High Performance …, 2016 | 86 | 2016 |
| A bottom–up model of spatial attention predicts human error patterns in rapid scene recognition W Einhäuser, TN Mundhenk, P Baldi, C Koch, L Itti Journal of Vision 7 (10), 6-6, 2007 | 52 | 2007 |
| Techniques for fisheye lens calibration using a minimal number of measurements TN Mundhenk, MJ Rivett, X Liao, EL Hall Intelligent Robots and Computer Vision XIX: Algorithms, Techniques, and …, 2000 | 46 | 2000 |
| Computational modeling and exploration of contour integration for visual saliency TN Mundhenk, L Itti Biological cybernetics 93 (3), 188-212, 2005 | 45 | 2005 |
| Efficient saliency maps for explainable AI TN Mundhenk, BY Chen, G Friedland arXiv preprint arXiv:1911.11293, 2019 | 44 | 2019 |
| Deep multi-modal vehicle detection in aerial ISR imagery W Sakla, G Konjevod, TN Mundhenk 2017 IEEE Winter Conference on Applications of Computer Vision (WACV), 916-923, 2017 | 43 | 2017 |
| Discovering symbolic policies with deep reinforcement learning DF Mikel Landajuela, Brenden K Petersen, Sookyung Kim, Claudio P Santiago ... International Conference on Machine Learning, 5979-5989, 2021 | 41 | 2021 |
| System for identifying regions of interest in visual imagery D Khosla, R Bhattacharyya, TN Mundhenk, DJ Huber US Patent 8,774,517, 2014 | 40 | 2014 |
| Backfilling points in a point cloud TN Mundhenk, Y Owechko, K Kim US Patent 9,811,880, 2017 | 39 | 2017 |
| Backfilling clouds of 3D coordinates TN Mundhenk, Y Owechko, K Kim US Patent 9,772,405, 2017 | 36 | 2017 |
| Predicting compressive strength of consolidated molecular solids using computer vision and deep learning B Gallagher, M Rever, D Loveland, TN Mundhenk, B Beauchamp, ... Materials & Design 190, 108541, 2020 | 33 | 2020 |
| System and method to improve object tracking using tracking fingerprints K Kim, C Jeong, TN Mundhenk, Y Owechko US Patent 9,940,726, 2018 | 33 | 2018 |
| Symbolic regression via deep reinforcement learning enhanced genetic programming seeding T Mundhenk, M Landajuela, R Glatt, CP Santiago, BK Petersen Advances in Neural Information Processing Systems 34, 24912-24923, 2021 | 25* | 2021 |
| A new robotics platform for neuromorphic vision: Beobots D Chung, R Hirata, TN Mundhenk, J Ng, RJ Peters, E Pichon, A Tsui, ... Biologically Motivated Computer Vision: Second International Workshop, BMCV …, 2002 | 24 | 2002 |
| Method and system for using fingerprints to track moving objects in video TN Mundhenk, K Kim, Y Owechko US Patent 8,811,670, 2014 | 19 | 2014 |
| Stereo-motion method of three-dimensional (3-D) structure information extraction from a video for fusion with 3-D point cloud data TN Mundhenk, HW Chen, Y Owechko, D Korchev, K Kim, Z Zhang US Patent 9,761,002, 2017 | 16 | 2017 |
Laurent IttiProfessor of Computer Science, University of Southern CaliforniaVerified email at usc.edu
