| Moving target classification and tracking from real-time video AJ Lipton, H Fujiyoshi, RS Patil Proceedings fourth IEEE workshop on applications of computer vision. WACV'98 …, 1998 | 2119 | 1998 |
| A system for video surveillance and monitoring RT Collins, AJ Lipton, T Kanade, H Fujiyoshi, D Duggins, Y Tsin, ... Technical Report, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA …, 2000 | 1853 | 2000 |
| Algorithms for cooperative multisensor surveillance RT Collins, AJ Lipton, H Fujiyoshi, T Kanade Proceedings of the IEEE 89 (10), 1456-1477, 2002 | 891 | 2002 |
| Real-time human motion analysis by image skeletonization H Fujiyoshi, AJ Lipton, T Kanade IEICE TRANSACTIONS on Information and Systems 87 (1), 113-120, 2004 | 738 | 2004 |
| Attention branch network: Learning of attention mechanism for visual explanation H Fukui, T Hirakawa, T Yamashita, H Fujiyoshi Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 684 | 2019 |
| Deep learning-based image recognition for autonomous driving H Fujiyoshi, T Hirakawa, T Yamashita IATSS research 43 (4), 244-252, 2019 | 588 | 2019 |
| A system for video surveillance and monitoring: VSAM final report R Collins, A Lipton, T Kanade, H Fujiyoshi, D Duggins, Y Tsin, D Tolliver, ... Technical report CMU-RI-TR-00-12, Robotics Institute, Carnegie Mellon University, 2000 | 520 | 2000 |
| Real-time human detection using relational depth similarity features S Ikemura, H Fujiyoshi Asian Conference on Computer Vision, 25-38, 2010 | 169 | 2010 |
| Boosted random forest Y Mishina, R Murata, Y Yamauchi, T Yamashita, H Fujiyoshi IEICE TRANSACTIONS on Information and Systems 98 (9), 1630-1636, 2015 | 154 | 2015 |
| Embedding human knowledge into deep neural network via attention map M Mitsuhara, H Fukui, Y Sakashita, T Ogata, T Hirakawa, T Yamashita, ... arXiv preprint arXiv:1905.03540, 2019 | 110 | 2019 |
| Pedestrian detection based on deep convolutional neural network with ensemble inference network H Fukui, T Yamashita, Y Yamauchi, H Fujiyoshi, H Murase 2015 IEEE Intelligent Vehicles Symposium (IV), 223-228, 2015 | 72 | 2015 |
| Visual explanation by attention branch network for end-to-end learning-based self-driving K Mori, H Fukui, T Murase, T Hirakawa, T Yamashita, H Fujiyoshi 2019 IEEE intelligent vehicles symposium (IV), 1577-1582, 2019 | 68 | 2019 |
| Can AI predict animal movements? Filling gaps in animal trajectories using inverse reinforcement learning T Hirakawa, T Yamashita, T Tamaki, H Fujiyoshi, Y Umezu, I Takeuchi, ... Ecosphere 9 (10), e02447, 2018 | 62 | 2018 |
| Object detection device H Fujiyoshi US Patent 8,611,604, 2013 | 62 | 2013 |
| Gradient-based feature extraction-SIFT and HOG H Fujiyoshi Computer 107 (206), 211-224, 2007 | 61 | 2007 |
| Virtual camerawork for generating lecture video from high resolution images T Yokoi, H Fujiyoshi 2005 IEEE International Conference on Multimedia and Expo, 4 pp., 2005 | 57 | 2005 |
| Evaluating feature importance for object classification in visual surveillance M Tsuchiya, H Fujiyoshi 18th International Conference on Pattern Recognition (ICPR'06) 2, 978-981, 2006 | 50 | 2006 |
| Survey on vision-based path prediction T Hirakawa, T Yamashita, T Tamaki, H Fujiyoshi International Conference on Distributed, Ambient, and Pervasive Interactions …, 2018 | 49 | 2018 |
| People detection based on co-occurrence of appearance and spatiotemporal features Y Yamauchi, H Fujiyoshi, BW Hwang, T Kanade 2008 19th International Conference on Pattern Recognition, 1-4, 2008 | 47 | 2008 |
| MT-DSSD: Deconvolutional single shot detector using multi task learning for object detection, segmentation, and grasping detection R Araki, T Onishi, T Hirakawa, T Yamashita, H Fujiyoshi 2020 IEEE International Conference on Robotics and Automation (ICRA), 10487 …, 2020 | 45 | 2020 |
Takayoshi YamashitaChubu UniversityVerified email at fsc.chubu.ac.jp
