His primary areas of study are Artificial intelligence, Computer vision, Image quality, Distortion and Visualization. The various areas that Guangtao Zhai examines in his Artificial intelligence study include Machine learning, Graphics, Metric and Pattern recognition. His work on Minimum description length as part of his general Pattern recognition study is frequently connected to Basis, thereby bridging the divide between different branches of science.
His Computer vision research incorporates themes from Entropy, Video quality and Perception. His Image quality study incorporates themes from Data mining, Image processing, Transform coding, Support vector machine and Feature extraction. His research in Feature extraction intersects with topics in Human visual system model and Scene statistics.
His primary scientific interests are in Artificial intelligence, Computer vision, Image quality, Pattern recognition and Distortion. His research combines Metric and Artificial intelligence. His research on Computer vision often connects related areas such as Algorithm.
The Image quality study which covers Histogram that intersects with Contrast. He has included themes like Artificial neural network and Deep learning in his Pattern recognition study. His research on Image processing focuses in particular on Digital image processing.
His main research concerns Artificial intelligence, Computer vision, Convolutional neural network, Pattern recognition and Image quality. He performs multidisciplinary study on Artificial intelligence and Distortion in his works. His studies in Computer vision integrate themes in fields like Pyramid and Visualization.
Guangtao Zhai interconnects Viewport, Weighting, Code, Feature learning and Algorithm in the investigation of issues within Convolutional neural network. Guangtao Zhai focuses mostly in the field of Pattern recognition, narrowing it down to topics relating to Salience and, in certain cases, Saliency map. His Image quality research includes elements of Noise, Quality assessment, Database and Human visual system model.
Guangtao Zhai focuses on Artificial intelligence, Computer vision, Image quality, Artificial neural network and Pattern recognition. Artificial intelligence connects with themes related to Machine learning in his study. His biological study focuses on Motion.
His Image quality research is multidisciplinary, incorporating elements of Mean opinion score, Quality assessment, Database and Distortion. His Artificial neural network study combines topics in areas such as Speech recognition, Quality of experience, Face and Perception. Guangtao Zhai incorporates Pattern recognition and Distortion in his research.
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.
Using free energy principle for blind image quality assessment
Ke Gu;Guangtao Zhai;Xiaokang Yang;Wenjun Zhang.
IEEE Transactions on Multimedia (2015)
The Analysis of Image Contrast: From Quality Assessment to Automatic Enhancement
Ke Gu;Guangtao Zhai;Weisi Lin;Min Liu.
IEEE Transactions on Systems, Man, and Cybernetics (2016)
A Deep Learning-Based Radiomics Model for Prediction of Survival in Glioblastoma Multiforme.
Jiangwei Lao;Yinsheng Chen;Zhi-Cheng Li;Qihua Li.
Scientific Reports (2017)
No-Reference Quality Assessment of Contrast-Distorted Images Based on Natural Scene Statistics
Yuming Fang;Kede Ma;Zhou Wang;Weisi Lin.
IEEE Signal Processing Letters (2015)
A Psychovisual Quality Metric in Free-Energy Principle
Guangtao Zhai;Xiaolin Wu;Xiaokang Yang;Weisi Lin.
IEEE Transactions on Image Processing (2012)
No-Reference Image Sharpness Assessment in Autoregressive Parameter Space
Ke Gu;Guangtao Zhai;Weisi Lin;Xiaokang Yang.
IEEE Transactions on Image Processing (2015)
No-Reference Quality Metric of Contrast-Distorted Images Based on Information Maximization
Ke Gu;Weisi Lin;Guangtao Zhai;Xiaokang Yang.
IEEE Transactions on Systems, Man, and Cybernetics (2017)
Saliency-Guided Quality Assessment of Screen Content Images
Ke Gu;Shiqi Wang;Huan Yang;Weisi Lin.
IEEE Transactions on Multimedia (2016)
Hybrid No-Reference Quality Metric for Singly and Multiply Distorted Images
Ke Gu;Guangtao Zhai;Xiaokang Yang;Wenjun Zhang.
IEEE Transactions on Broadcasting (2014)
Automatic Contrast Enhancement Technology With Saliency Preservation
Ke Gu;Guangtao Zhai;Xiaokang Yang;Wenjun Zhang.
IEEE Transactions on Circuits and Systems for Video Technology (2015)
Shanghai Jiao Tong University
Beijing University of Technology
Shanghai Jiao Tong University
Nanyang Technological University
McMaster University
Verizon (United States)
Harbin Institute of Technology
Peking University
University at Buffalo, State University of New York
City University of Hong Kong
Profile was last updated on December 6th, 2021.
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