| Distributed recurrent neural networks for cooperative control of manipulators: A game-theoretic perspective S Li, J He, Y Li, MU Rafique IEEE transactions on neural networks and learning systems 28 (2), 415-426, 2016 | 289 | 2016 |
| Evaluation of segmentation methods on head and neck CT: auto‐segmentation challenge 2015 PF Raudaschl, P Zaffino, GC Sharp, MF Spadea, A Chen, BM Dawant, ... Medical physics 44 (5), 2020-2036, 2017 | 267 | 2017 |
| Nonlinearly activated neural network for solving time-varying complex Sylvester equation S Li, Y Li IEEE transactions on cybernetics 44 (8), 1397-1407, 2013 | 220 | 2013 |
| Neural dynamics for cooperative control of redundant robot manipulators L Jin, S Li, X Luo, Y Li, B Qin IEEE Transactions on Industrial Informatics 14 (9), 3812-3821, 2018 | 189 | 2018 |
| Decentralized kinematic control of a class of collaborative redundant manipulators via recurrent neural networks S Li, S Chen, B Liu, Y Li, Y Liang Neurocomputing 91, 1-10, 2012 | 183 | 2012 |
| A class of finite-time dual neural networks for solving quadratic programming problems and its k-winners-take-all application S Li, Y Li, Z Wang Neural Networks 39, 27-39, 2013 | 160 | 2013 |
| Extracting general-purpose features from LIDAR data Y Li, EB Olson 2010 IEEE international conference on robotics and automation, 1388-1393, 2010 | 140 | 2010 |
| LMTRDA: Using logistic model tree to predict MiRNA-disease associations by fusing multi-source information of sequences and similarities L Wang, ZH You, X Chen, YM Li, YN Dong, LP Li, K Zheng PLoS computational biology 15 (3), e1006865, 2019 | 120 | 2019 |
| Selective positive–negative feedback produces the winner-take-all competition in recurrent neural networks S Li, B Liu, Y Li IEEE transactions on neural networks and learning systems 24 (2), 301-309, 2012 | 109 | 2012 |
| GCNCDA: a new method for predicting circRNA-disease associations based on graph convolutional network algorithm L Wang, ZH You, YM Li, K Zheng, YA Huang PLOS Computational Biology 16 (5), e1007568, 2020 | 107 | 2020 |
| Dcr-net: A deep co-interactive relation network for joint dialog act recognition and sentiment classification L Qin, W Che, Y Li, M Ni, T Liu Proceedings of the AAAI conference on artificial intelligence 34 (05), 8665-8672, 2020 | 92 | 2020 |
| Decentralized control of collaborative redundant manipulators with partial command coverage via locally connected recurrent neural networks S Li, H Cui, Y Li, B Liu, Y Lou Neural Computing and Applications 23, 1051-1060, 2013 | 81 | 2013 |
| Using laplacian eigenmap as heuristic information to solve nonlinear constraints defined on a graph and its application in distributed range-free localization of wireless … S Li, Z Wang, Y Li Neural processing letters 37, 411-424, 2013 | 69 | 2013 |
| Fast and robust data association using posterior based approximate joint compatibility test Y Li, S Li, Q Song, H Liu, MQH Meng IEEE Transactions on Industrial Informatics 10 (1), 331-339, 2013 | 62 | 2013 |
| Structure tensors for general purpose LIDAR feature extraction Y Li, EB Olson 2011 IEEE International Conference on Robotics and Automation, 1869-1874, 2011 | 61 | 2011 |
| A general purpose feature extractor for light detection and ranging data Y Li, EB Olson Sensors 10 (11), 10356-10375, 2010 | 61 | 2010 |
| Gaussian process regression for sensorless grip force estimation of cable-driven elongated surgical instruments Y Li, B Hannaford IEEE robotics and automation letters 2 (3), 1312-1319, 2017 | 59 | 2017 |
| Discrete computational neural dynamics models for solving time-dependent Sylvester equation with applications to robotics and MIMO systems Y Qi, L Jin, H Li, Y Li, M Liu IEEE Transactions on Industrial Informatics 16 (10), 6231-6241, 2020 | 57 | 2020 |
| Hysteresis model of longitudinally loaded cable for cable driven robots and identification of the parameters M Miyasaka, M Haghighipanah, Y Li, B Hannaford 2016 IEEE International Conference on Robotics and Automation (ICRA), 4051-4057, 2016 | 53 | 2016 |
| Surgical instrument segmentation for endoscopic vision with data fusion of cnn prediction and kinematic pose F Qin, Y Li, YH Su, D Xu, B Hannaford 2019 international conference on robotics and automation (ICRA), 9821-9827, 2019 | 52 | 2019 |
Blake HannafordProfessor of Electrical Engineering, University of Washington在 uw.edu 的电子邮件经过验证
