The publication list is categorised according to the research topics. You can also refer to google scholar.

[11] F Shokrollahi Yancheshmeh, K Chen, JK Kämäräinen, Unsupervised Visual Alignment with Similarity Graphs, Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, 2015.

[10] E Riabchenko, K Chen, JK Kämäräinen, Progressive Visual Object Detection with Positive Training Examples Only, Proceedings of Scandinavian Conference on Image Analysis, 2015.

[9] H. Huttunen, K Chen, A. Thakur, A. Krohn-Grimberghe, O. Gencoglu, X. Ni, M. Al-Musawi, L. Xu, H. Jacob van Veen, Computer Vision for Head Pose Estimation: Review of a Competition, Proceedings of Scandinavian Conference on Image Analysis, 2015.

[8] F Shokrollahi Yancheshmeh, JK Kämäräinen, K Chen, Discovering Multi-Relational Latent Attributes by Visual Similarity Networks, Proceedings of Asian Conference on Computer Vision Workshop on Feature and Similarity, 2014.

[7] E Riabchenko, JK Kämäräinen, K Chen, Learning Generative Models of Object Parts from A Few Positive Examples, Proceedings of International Conference on Pattern Recognition, pp. 2287-2292, 2014.

[6] E Riabchenko, JK Kämäräinen, K Chen, Density-Aware Part-Based Object Detection with Positive Examples, Proceedings of International Conference on Pattern Recognition, pp. 2814-2819 , 2014.

[5] K Chen, JK Kämäräinen, Learning to Count with Back-Propagated Information, Proceedings of International Conference on Pattern Recognition, pp. 4672-4677, 2014.

[4] K Chen, S Gong, T Xiang, CC Loy, Cumulative Attribute Space for Age and Crowd Density Estimation, Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, pp. 2467-2474, 2013. (Oral) pdf slides poster project page

[3] CC Loy, K Chen, S Gong, T Xiang, Crowd Counting and Profiling: Methodology and Evaluation, in S. Ali, K. Nishino, D. Manocha, and M. Shah (Eds.), Modeling, Simulation, and Visual Analysis of Large Crowds, Springer, 2013. pdf

[2] K Chen, CC Loy, S Gong, T Xiang, Feature Mining for Localised Crowd Counting, Proceedings of British Machine Vision Conference, pp. 21.1-21.11, 2012. pdf poster project page

[1] K Chen, S Gong, T Xiang, Human Pose Estimation Using Structural Support Vector Machines, Proceedings of IEEE International Conference on Computer Vision, Workshop on Socially Intelligent Surveillance and Monitoring, pp. 846-851, 2011. pdf

[28] Y Zhang, Z Xiao, K Chen, M Mao, X Liu, Analysis of G-Type Model Exploited for Online ZLE Solving, Proceedings of The 26th Chinese Control and Decision Conference, pp. 166–171, 2014.

[27] K Chen, Recurrent Implicit Dynamics for Online Matrix Inversion, Applied Mathematics and Computation, vol. 219, no. 20, pp. 10218–10224, 2013. pdf

[26] K Chen, Implicit Dynamic System for Online Simultaneous Linear Equations Solving, Electronics Letters, vol. 49, no. 2, pp. 101-102, 2013. pdf

[25] K Chen, Robustness Analysis of Wang Neural Network for Online Linear Equation Solving, Electronics Letters, vol. 48, no. 22, pp. 1931-1932, 2012. pdf

[24] Y Zhang, D Guo, B Cai, K Chen, Remedy Scheme and Theoretical Analysis of Joint-Angle Drift Phenomenon for Redundant Robot Manipulators, Robotics and Computer-Integrated Manufacturing, vol. 27, no. 4, pp. 860-869, 2011. pdf

[23] Y Zhang, K Chen, HZ Tan, Performance Analysis of Gradient Neural Network Exploited for Online Time-Varying Matrix Inversion, IEEE Transactions on Automatic Control, vol. 54, no. 8, pp. 1940-1945, 2009. pdf

[22] Y Zhang, Z Chen, K Chen, Convergence Properties Analysis of Gradient Neural Network for Solving Online Linear Equations, Acta Automatica Sinica, vol. 35, no. 8, pp. 1136-1139, 2009. pdf

[21] Y Zhang, Y Shi, K Chen, C Wang, Global Exponential Convergence and Stability of Gradient-Based Neural Network for Online Matrix Inversion, Applied Mathematics and Computation, vol. 215, no. 3, pp. 1301-1306, 2009. pdf

[20] Y Zhang, Z Tan, K Chen, Z Yang, X Lv, Repetitive Motion of Redundant Robots Planned by Three Kinds of Recurrent Neural Networks and Illustrated with a Four-Link Planar Manipulator’s Straight-Line Example, Robotics and Autonomous Systems, vol. 57, no. 6, pp. 645-651, 2009. pdf

[19] Y Zhang, W Ma, XD Li, HZ Tan, K Chen, MATLAB Simulink Modeling and Simulation of LVI-based Primal–Dual Neural Network for Solving Linear and Quadratic Programs, Neurocomputing, vol. 72, no. 7, pp. 1679-1687, 2009. pdf

[18] N Tan, K Chen, Y Shi, Y Zhang, Modeling, Verification and Comparison of Zhang Neural Net and Gradient Neural Net for Online Solution of Time-Varying Linear Matrix Equation, Proceedings of IEEE Conference on Industrial Electronics and Applications, pp. 3698-3703, 2009. pdf

[17] K Chen, D Guo, Z Tan, Z Yang, Y Zhang, Cyclic Motion Planning of Redundant Robot Arms: Simple Extension of Performance Index May Not Work, Proceedings of International Symposium on Intelligent Information Technology Application, pp. 635-639, 2008. pdf

[16] K Chen, L Zhang, Y Zhang, Cyclic Motion Generation of Multi-Link Planar Robot Performing Square End-Effector Trajectory Analyzed via Gradient-Descent and Zhang et al’s Neural-Dynamic Methods, Proceedings of International Symposium on Systems and Control in Aerospace and Astronautics, pp. 1-6, 2008. pdf

[15] Y Zhang, X Lv, Z Li, Z Yang, K Chen, Repetitive Motion Planning of PA10 Robot Arm Subject to Joint Physical Limits and Using LVI-Based Primal–Dual Neural Network, Mechatronics, vol. 18, no. 9, pp. 475-485, 2008. pdf

[14] Y Zhang, K Chen, X Li, C Yi, H Zhu, Simulink Modeling and Comparison of Zhang Neural Networks and Gradient Neural Networks for Time-Varying Lyapunov Equation Solving, Proceedings of International Conference on Natural Computation, pp. 521-525, 2008. pdf

[13] Y Zhang, Z Tan, Z Yang, X Lv, K Chen, A Simplified LVI-Based Primal-Dual Neural Network for Repetitive Motion Planning of PA10 Robot Manipulator Starting from Different Initial States, Proceedings of IEEE International Joint Conference on Neural Networks, pp. 19-24, 2008. pdf

[12] Y Zhang, Z Chen, K Chen, B Cai, Zhang Neural Network Without Using Time-Derivative Information for Constant and Time-Varying Matrix Inversion, Proceedings of IEEE International Joint Conference on Neural Networks, pp. 142-146, 2008. pdf

[11] Y Zhang, W Li, C Yi, K Chen, A Weights-Directly-Determined Simple Neural Network for Nonlinear System Identification, Proceedings of IEEE International Conference on Fuzzy Systems, pp. 455-460, 2008. pdf

[10] Y Zhang, K Chen, Comparison on Zhang Neural Network and Gradient Neural Network for Time-Varying Linear Matrix Equation AXB= C Solving, Proceedings of IEEE International Conference on Industrial Technology, pp. 1-6, 2008. (Student Scholarship Awarded by IEEE Industrial Technology Society) pdf

[9] Y Zhang, X Guo, W Ma, K Chen, B Cai, MATLAB Simulink Modeling and Simulation of Zhang Neural Network for Online Time-Varying Matrix Inversion, Proceedings of IEEE International Conference on Networking, Sensing and Control, pp. 1480-1485, 2008. pdf

[8] Y Zhang, Z Li, K Chen, B Cai, Common Nature of Learning Exemplified by BP and Hopfield Neural Networks for Solving Online a System of Linear Equations, Proceedings of IEEE International Conference on Networking, Sensing and Control, pp. 832-836, 2008. pdf

[7] Y Zhang, K Chen, Global Exponential Convergence and Stability of Wang Neural Network for Solving Online Linear Equations, Electronics Letters, vol. 44, no. 2, pp. 145-146, 2008. pdf

[6] K Chen, S Yue, Y Zhang, MATLAB Simulation and Comparison of Zhang Neural Network and Gradient Neural Network for Online Solution of Linear Time-Varying Matrix Equation AXB− C= 0, Proceedings of International Conference on Intelligent Computing, pp. 68-75, 2008. pdf

[5] Y Zhang, Z Li, C Yi, K Chen, Zhang Neural Network Versus Gradient Neural Network for Online Time-Varying Quadratic Function Minimization, International Conference on Intelligent Computing, pp. 807-814, 2008. pdf

[4] Y Zhang, S Yue, K Chen, C Yi, MATLAB Simulation and Comparison of Zhang Neural Network and Gradient Neural Network for Time-Varying Lyapunov Equation Solving, Proceedings of International Symposium on Neural Networks, pp. 117-127, 2008. pdf

[3] Y Zhang, K Chen, W Ma, XD Li, MATLAB Simulation of Gradient-Based Neural Network for Online Matrix Inversion, Proceedings of International Conference on Intelligent Computing, pp. 98-109, 2007. pdf code

[2] Y Zhang, W Ma K Chen, P Li, MATLAB Simulation of Zhang Neural Networks for Time-Varying Sylvester Equation Solving, Proceedings of International Conference on Information Computing and Automation, pp. 392-395, 2007. pdf

[1] Y Zhang, K Chen, W Ma, MATLAB Simulation and Comparison of Zhang Neural Network and Gradient Neural Network of Online Solution of Linear Time-Varying Equations, Proceedings of International Conference on Life System Modeling and Simulation, pp. 450-454, 2007. pdf

[C5] 张雨浓, 史艳燕, 蔡炳煌, 张禹珩, 陈轲, 梯度神经网络解线性矩阵方程之收敛性分析, 控制工程, vol. 19, no. 2, pp. 235-239, 2012. pdf

[C4] 张雨浓, 杨逸文, 陈轲, 蔡炳煌, 梯度神经网络求解Sylvester方程之MATLAB仿真, 系统仿真学报, vol. 21, no. 13, pp. 4028-4031, 2009. pdf

[C3] 张雨浓, 陈轲, 过晓娇, 指导本科生从事科学研究的尝试,经验与探讨, 科技成果管理与研究, no. 6, pp. 19-22, 2009. pdf

[C2] 张雨浓, 张禹珩, 陈轲, 蔡炳煌, 马伟木, 线性矩阵方程的梯度法神经网络求解及其仿真验证, 中山大学学报: 自然科学版, vol. 47, no. 3, pp. 26-32, 2008. pdf

[C1] 张雨浓, 李巍, 刘巍, 谭满春, 陈轲, 幂激励前向神经网络的权值直接确定法, 全国模式识别学术会议, pp. 72-77, 2007. pdf