His primary areas of investigation include Artificial neural network, Artificial intelligence, Pattern recognition, Mathematical optimization and Recurrent neural network. His Artificial neural network research is multidisciplinary, incorporating elements of Discrete time and continuous time, Control theory, Invariant, Applied mathematics and Topology. His biological study spans a wide range of topics, including Margin and Machine learning.
His studies in Pattern recognition integrate themes in fields like Data mining, Cluster analysis, Facial recognition system, Effective algorithm and Mean vector. His Mathematical optimization study integrates concerns from other disciplines, such as CURE data clustering algorithm and Subspace topology. His work is dedicated to discovering how Recurrent neural network, Attractor are connected with Invariant measure and Linear system and other disciplines.
Artificial intelligence, Artificial neural network, Pattern recognition, Algorithm and Mathematical optimization are his primary areas of study. His Artificial intelligence study combines topics from a wide range of disciplines, such as Machine learning and Computer vision. Zhang Yi studies Artificial neural network, namely Recurrent neural network.
In his study, Sparse approximation is strongly linked to Subspace topology, which falls under the umbrella field of Pattern recognition. His Algorithm research includes themes of Stability, Discrete time and continuous time, Cluster analysis, Invariant and Constant. Zhang Yi combines subjects such as Graph and Data mining with his study of Cluster analysis.
The scientist’s investigation covers issues in Artificial intelligence, Pattern recognition, Artificial neural network, Deep neural networks and Segmentation. Zhang Yi works mostly in the field of Artificial intelligence, limiting it down to topics relating to Machine learning and, in certain cases, Inference, as a part of the same area of interest. His Pattern recognition study deals with Breast cancer intersecting with Binary classification.
His Artificial neural network research integrates issues from Transfer of learning, Relation and Attractor, Topology. His Deep neural networks research incorporates themes from Data-driven, Ultrasonography and Thyroid cancer. His work deals with themes such as Multi-task learning, Surgical planning, Planning target volume and Dose prediction, which intersect with Segmentation.
Zhang Yi mainly focuses on Artificial intelligence, Pattern recognition, Deep neural networks, Convolutional neural network and Robustness. His Artificial neural network study in the realm of Artificial intelligence connects with subjects such as Stage. Zhang Yi has included themes like Multimedia and Medical imaging in his Artificial neural network study.
The various areas that Zhang Yi examines in his Deep neural networks study include Optical coherence tomography, Ultrasonography, Overfitting and Ultrasound. His Convolutional neural network research incorporates elements of Breast cancer, Fundus and Sensitivity. The concepts of his Robustness study are interwoven with issues in Learning rule, Robust optimization, Multiobjective optimization problem and Pareto optimal.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Advances in Neural Networks - ISNN 2006
Jun Wang;Zhang Yi;Jacek M. Zurada;Bao-Liang Lu.
international symposium on neural networks (2006)
Advances in Neural Networks — ISNN 2005
Jun Wang;Xiao-Feng Liao;Zhang Yi.
Lecture Notes in Computer Science (2005)
Stability of fuzzy control systems with bounded uncertain delays
Zhang Yi;Pheng Ann Heng.
IEEE Transactions on Fuzzy Systems (2002)
Convergence analysis of cellular neural networks with unbounded delay
Zhang Yi;Pheng Ann Heng;Kwong Sak Leung.
IEEE Transactions on Circuits and Systems I-regular Papers (2001)
Fuzzy SVM with a new fuzzy membership function
Xiufeng Jiang;Zhang Yi;Jian Cheng Lv.
Neural Computing and Applications (2006)
Letters: A hierarchical intrusion detection model based on the PCA neural networks
Guisong Liu;Zhang Yi;Shangming Yang.
Constructing the L2-Graph for Robust Subspace Learning and Subspace Clustering
Xi Peng;Zhiding Yu;Zhang Yi;Huajin Tang.
IEEE Transactions on Systems, Man, and Cybernetics (2017)
Deep subspace clustering with sparsity prior
Xi Peng;Shijie Xiao;Jiashi Feng;Wei-Yun Yau.
international joint conference on artificial intelligence (2016)
Neural Networks: Computational Models and Applications
Huajin Tang;Kay Chen Tan;Zhang Yi.
Multistability of discrete-time recurrent neural networks with unsaturating piecewise linear activation functions
Zhang Yi;Kok Kiong Tan.
IEEE Transactions on Neural Networks (2004)
Profile was last updated on December 6th, 2021.
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