What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Machine learning
- Artificial neural network
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.
His most cited work include:
- Advances in Neural Networks - ISNN 2006 (203 citations)
- Stability of fuzzy control systems with bounded uncertain delays (200 citations)
- Advances in Neural Networks — ISNN 2005 (182 citations)
What are the main themes of his work throughout his whole career to date?
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.
He most often published in these fields:
- Artificial intelligence (51.33%)
- Artificial neural network (37.67%)
- Pattern recognition (30.67%)
What were the highlights of his more recent work (between 2018-2021)?
- Artificial intelligence (51.33%)
- Pattern recognition (30.67%)
- Artificial neural network (37.67%)
In recent papers he was focusing on the following fields of study:
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.
Between 2018 and 2021, his most popular works were:
- IGD Indicator-Based Evolutionary Algorithm for Many-Objective Optimization Problems (110 citations)
- Automated diagnosis of breast ultrasonography images using deep neural networks. (50 citations)
- A Novel Deep Learning-Based Collaborative Filtering Model for Recommendation System (46 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Machine learning
- Artificial neural network
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.
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