Ying He mainly investigates Solid modeling, Topology, Algorithm, Artificial intelligence and Polycube. His Solid modeling study combines topics in areas such as Visualization, Distance transform and Spline. As a part of the same scientific study, he usually deals with the Topology, concentrating on Curve fitting and frequently concerns with Gravitational singularity and Parametrization.
The Algorithm study combines topics in areas such as Geometric primitive, Solid geometry, Computer graphics and Geodesic. His Artificial intelligence research is multidisciplinary, incorporating perspectives in Machine learning, Computer vision and Pattern recognition. Ying He interconnects Divide and conquer algorithms, Hexahedron and Bijection in the investigation of issues within Polycube.
Ying He mainly focuses on Artificial intelligence, Algorithm, Computer vision, Topology and Polygon mesh. Much of his study explores Artificial intelligence relationship to Pattern recognition. The concepts of his Algorithm study are interwoven with issues in Point cloud, Surface and Solid modeling.
His Solid modeling research is multidisciplinary, relying on both Polycube and Spline. Computer vision is closely attributed to Computer graphics in his work. His research investigates the connection between Polygon mesh and topics such as Geodesic that intersect with problems in Time complexity and Voronoi diagram.
His primary areas of investigation include Algorithm, Artificial intelligence, Point cloud, Point and Polygon mesh. Ying He works in the field of Algorithm, namely Computation. His work carried out in the field of Artificial intelligence brings together such families of science as Distraction, Computer vision and Pattern recognition.
His Computer vision study integrates concerns from other disciplines, such as Grid and Projection. In his study, which falls under the umbrella issue of Pattern recognition, Topology, Net and Graph is strongly linked to Vertex. His studies in Polygon mesh integrate themes in fields like Smoothing, Vertex and Geodesic.
His main research concerns Algorithm, Polygon mesh, Point cloud, Geodesic and Point. His research integrates issues of Smoothing, Solver and Artificial intelligence in his study of Algorithm. The various areas that he examines in his Artificial intelligence study include Iterative method, Computation and Code.
His Polygon mesh research includes themes of Discrete mathematics, Time complexity and Vertex. He has included themes like Distance transform and Quadratic programming in his Geodesic study. His research on Point also deals with topics like
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Wireless Sensor Networks
Miao Jin;Xianfeng Gu;Ying He;Yalin Wang.
Hongyu Wang;Ying He;Xin Li;Xianfeng Gu.
Computer-aided Design (2008)
A Review of the Functional and Anatomical Default Mode Network in Schizophrenia.
Mao-Lin Hu;Mao-Lin Hu;Xiao-Fen Zong;Xiao-Fen Zong;J. John Mann;Jun-Jie Zheng.
Neuroscience Bulletin (2017)
Xianfeng Gu;Ying He;Hong Qin.
solid and physical modeling (2005)
Harmonic volumetric mapping for solid modeling applications
Xin Li;Xiaohu Guo;Hongyu Wang;Ying He.
solid and physical modeling (2007)
Human behaviour as an aspect of cybersecurity assurance
Mark Evans;Leandros A. Maglaras;Ying He;Helge Janicke.
Security and Communication Networks (2016)
Social Internet of Vehicles for Smart Cities
Leandros Maglaras;Ali Hilal Al-Bayatti;Ying He;Isabel Wagner.
Journal of Sensor and Actuator Networks (2016)
Retrieval-Based Face Annotation by Weak Label Regularized Local Coordinate Coding
Dayong Wang;Steven C. H. Hoi;Ying He;Jianke Zhu.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2014)
Manifold SLIC: A Fast Method to Compute Content-Sensitive Superpixels
Yong-Jin Liu;Cheng-Chi Yu;Min-Jing Yu;Ying He.
computer vision and pattern recognition (2016)
A branch-estimation-based state estimation method for radial distribution systems
Youman Deng;Ying He;Boming Zhang.
IEEE Power & Energy Magazine (2002)
Profile was last updated on December 6th, 2021.
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