D-Index & Metrics Best Publications

D-Index & Metrics

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Computer Science D-index 44 Citations 7,635 316 World Ranking 3803 National Ranking 351

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Computer vision
  • Statistics

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 most cited work include:

  • Using free energy principle for blind image quality assessment (361 citations)
  • A Deep Learning-Based Radiomics Model for Prediction of Survival in Glioblastoma Multiforme. (218 citations)
  • The Analysis of Image Contrast: From Quality Assessment to Automatic Enhancement (211 citations)

What are the main themes of his work throughout his whole career to date?

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.

He most often published in these fields:

  • Artificial intelligence (73.33%)
  • Computer vision (52.80%)
  • Image quality (30.40%)

What were the highlights of his more recent work (between 2019-2021)?

  • Artificial intelligence (73.33%)
  • Computer vision (52.80%)
  • Convolutional neural network (6.13%)

In recent papers he was focusing on the following fields of study:

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.

Between 2019 and 2021, his most popular works were:

  • Abnormal respiratory patterns classifier may contribute to large-scale screening of people infected with COVID-19 in an accurate and unobtrusive manner. (76 citations)
  • How is Gaze Influenced by Image Transformations? Dataset and Model (22 citations)
  • Learning To Blindly Assess Image Quality In The Laboratory And Wild (15 citations)

In his most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Computer vision
  • Statistics

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.

Best Publications

Using free energy principle for blind image quality assessment

Ke Gu;Guangtao Zhai;Xiaokang Yang;Wenjun Zhang.
IEEE Transactions on Multimedia (2015)

412 Citations

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)

268 Citations

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)

262 Citations

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)

242 Citations

A Psychovisual Quality Metric in Free-Energy Principle

Guangtao Zhai;Xiaolin Wu;Xiaokang Yang;Weisi Lin.
IEEE Transactions on Image Processing (2012)

218 Citations

No-Reference Image Sharpness Assessment in Autoregressive Parameter Space

Ke Gu;Guangtao Zhai;Weisi Lin;Xiaokang Yang.
IEEE Transactions on Image Processing (2015)

200 Citations

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)

185 Citations

Saliency-Guided Quality Assessment of Screen Content Images

Ke Gu;Shiqi Wang;Huan Yang;Weisi Lin.
IEEE Transactions on Multimedia (2016)

179 Citations

Hybrid No-Reference Quality Metric for Singly and Multiply Distorted Images

Ke Gu;Guangtao Zhai;Xiaokang Yang;Wenjun Zhang.
IEEE Transactions on Broadcasting (2014)

170 Citations

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)

164 Citations

Best Scientists Citing Guangtao Zhai

Weisi Lin

Weisi Lin

Nanyang Technological University

Publications: 88

Ke Gu

Ke Gu

Beijing University of Technology

Publications: 66

Shiqi Wang

Shiqi Wang

City University of Hong Kong

Publications: 39

Yuming Fang

Yuming Fang

Jiangxi University of Finance and Economics

Publications: 39

Guangming Shi

Guangming Shi

Xidian University

Publications: 32

Siwei Ma

Siwei Ma

Peking University

Publications: 27

Debin Zhao

Debin Zhao

Harbin Institute of Technology

Publications: 26

Wen Gao

Wen Gao

Peking University

Publications: 25

Xiaolin Wu

Xiaolin Wu

McMaster University

Publications: 24

Alan C. Bovik

Alan C. Bovik

The University of Texas at Austin

Publications: 24

King Ngi Ngan

King Ngi Ngan

University of Electronic Science and Technology of China

Publications: 23

Junfei Qiao

Junfei Qiao

Beijing University of Technology

Publications: 20

Zhou Wang

Zhou Wang

University of Waterloo

Publications: 19

Hongliang Li

Hongliang Li

University of Electronic Science and Technology of China

Publications: 17

Xiaokang Yang

Xiaokang Yang

Shanghai Jiao Tong University

Publications: 14

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking d-index is inferred from publications deemed to belong to the considered discipline.

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