2014 - IEEE Fellow For contributions to optimization techniques in cybernetics and video coding
Sam Kwong mostly deals with Artificial intelligence, Algorithm, Mathematical optimization, Benchmark and Machine learning. His Artificial intelligence research includes themes of Speech recognition, Computer vision and Pattern recognition. His studies in Algorithm integrate themes in fields like Encoder and Integer dct.
He works mostly in the field of Mathematical optimization, limiting it down to concerns involving Convergence and, occasionally, Optimization problem and Particle swarm optimization. The Machine learning study combines topics in areas such as Classifier and Fuzzy set. The concepts of his Multi-objective optimization study are interwoven with issues in Evolutionary computation and Selection.
His primary scientific interests are in Artificial intelligence, Algorithm, Pattern recognition, Computer vision and Mathematical optimization. His Artificial intelligence study integrates concerns from other disciplines, such as Machine learning and Speech recognition. In Algorithm, Sam Kwong works on issues like Coding, which are connected to Video quality.
As a member of one scientific family, Sam Kwong mostly works in the field of Pattern recognition, focusing on Cluster analysis and, on occasion, Data mining. Mathematical optimization and Benchmark are frequently intertwined in his study. His research integrates issues of Convergence and Selection in his study of Multi-objective optimization.
Sam Kwong spends much of his time researching Artificial intelligence, Pattern recognition, Algorithm, Computer vision and Image. The Classifier research Sam Kwong does as part of his general Pattern recognition study is frequently linked to other disciplines of science, such as Domain, therefore creating a link between diverse domains of science. His Algorithm study combines topics in areas such as Point cloud, Random access, Distortion, Upsampling and Coding.
His Coding research is multidisciplinary, relying on both Encoder, Rate–distortion optimization and Data compression. His study in the fields of Light field and Stereoscopy under the domain of Computer vision overlaps with other disciplines such as Underwater. His research in Benchmark intersects with topics in Convergence and Optimization problem, Particle swarm optimization, Mathematical optimization.
Artificial intelligence, Algorithm, Benchmark, Pattern recognition and Mathematical optimization are his primary areas of study. He has researched Artificial intelligence in several fields, including Field and Computer vision. His study on Computational complexity theory is often connected to Differentiable function as part of broader study in Algorithm.
His Benchmark study incorporates themes from Evolutionary computation, Evolutionary algorithm and Differential evolution. His Pattern recognition study combines topics from a wide range of disciplines, such as Precision and recall, Hash function, Hash table and Image retrieval. His Multi-objective optimization, Particle swarm optimization and Memetic algorithm study in the realm of Mathematical optimization connects with subjects such as Domain and Test suite.
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.
Genetic algorithms: concepts and applications [in engineering design]
K.F. Man;K.S. Tang;S. Kwong.
IEEE Transactions on Industrial Electronics (1996)
Gbest-guided artificial bee colony algorithm for numerical function optimization
Guopu Zhu;Sam Kwong.
Applied Mathematics and Computation (2010)
Genetic algorithms and their applications
K.S. Tang;K.F. Man;S. Kwong;Q. He.
IEEE Signal Processing Magazine (1996)
Genetic Algorithms: Concepts and Applications
K. F. Man;K. S. Tang;S. Kwong.
An Evolutionary Many-Objective Optimization Algorithm Based on Dominance and Decomposition
Ke Li;Kalyanmoy Deb;Qingfu Zhang;Sam Kwong.
IEEE Transactions on Evolutionary Computation (2015)
An information-based sequence distance and its application to whole mitochondrial genome phylogeny
Ming Li;Jonathan H. Badger;Xin Chen;Sam Kwong.
An optimal fuzzy PID controller
K.S. Tang;Kim Fung Man;Guanrong Chen;S. Kwong.
IEEE Transactions on Industrial Electronics (2001)
A Compression Algorithm for DNA Sequences and Its Applications in Genome Comparison.
Xin Chen;Sam Kwong;Ming Li.
Genome Informatics (1999)
Efficient Motion and Disparity Estimation Optimization for Low Complexity Multiview Video Coding
Zhaoqing Pan;Yun Zhang;Sam Kwong.
IEEE Transactions on Broadcasting (2015)
Adaptive Operator Selection With Bandits for a Multiobjective Evolutionary Algorithm Based on Decomposition
Ke Li;Alvaro Fialho;Sam Kwong;Qingfu Zhang.
IEEE Transactions on Evolutionary Computation (2014)
Profile was last updated on December 6th, 2021.
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