H-Index & Metrics Best Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science D-index 121 Citations 65,837 749 World Ranking 47 National Ranking 5

Research.com Recognitions

Awards & Achievements

2006 - Fellow of the International Association for Pattern Recognition (IAPR) For contributions to biometrics technologies and systems.

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Gene
  • Computer vision

His primary areas of investigation include Artificial intelligence, Pattern recognition, Computer vision, Feature extraction and Biometrics. His Artificial intelligence research includes themes of Machine learning and Identification. His studies in Pattern recognition integrate themes in fields like Contextual image classification and Image.

His work on Computer vision is being expanded to include thematically relevant topics such as Matching. His Feature extraction study which covers Subspace topology that intersects with Linear subspace. His Biometrics research includes elements of Matching, Orientation, Line and Authentication.

His most cited work include:

  • Two-dimensional PCA: a new approach to appearance-based face representation and recognition (2969 citations)
  • FSIM: A Feature Similarity Index for Image Quality Assessment (2515 citations)
  • A Completed Modeling of Local Binary Pattern Operator for Texture Classification (1469 citations)

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

Artificial intelligence, Pattern recognition, Computer vision, Feature extraction and Biometrics are his primary areas of study. His Artificial intelligence study frequently intersects with other fields, such as Machine learning. His study on Pattern recognition is mostly dedicated to connecting different topics, such as Speech recognition.

His Tongue research extends to Computer vision, which is thematically connected. His research on Feature extraction often connects related areas such as Contextual image classification. His Biometrics research is multidisciplinary, incorporating perspectives in Matching, Data mining, Identification and Authentication.

He most often published in these fields:

  • Artificial intelligence (60.88%)
  • Pattern recognition (42.84%)
  • Computer vision (23.70%)

What were the highlights of his more recent work (between 2017-2021)?

  • Artificial intelligence (60.88%)
  • Pattern recognition (42.84%)
  • Feature extraction (21.15%)

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

David Zhang mainly focuses on Artificial intelligence, Pattern recognition, Feature extraction, Algorithm and Discriminative model. The study of Artificial intelligence is intertwined with the study of Computer vision in a number of ways. His Pattern recognition study combines topics from a wide range of disciplines, such as Latent variable, Subspace topology, Minutiae and Robustness.

The concepts of his Algorithm study are interwoven with issues in Signal, Image compression and Trigonometric functions. While the research belongs to areas of Sparse approximation, David Zhang spends his time largely on the problem of Facial recognition system, intersecting his research to questions surrounding Categorization. His research in Biometrics intersects with topics in Identifier and Authentication.

Between 2017 and 2021, his most popular works were:

  • Learning Convolutional Networks for Content-Weighted Image Compression (169 citations)
  • A Trilateral Weighted Sparse Coding Scheme for Real-World Image Denoising (93 citations)
  • Learning Domain-Invariant Subspace Using Domain Features and Independence Maximization. (83 citations)

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

  • Artificial intelligence
  • Gene
  • Cancer

David Zhang focuses on Artificial intelligence, Pattern recognition, Algorithm, Feature extraction and Discriminative model. In his study, Limit is inextricably linked to Computer vision, which falls within the broad field of Artificial intelligence. His Pattern recognition research is multidisciplinary, incorporating elements of Feature, Representation, Contextual image classification, Norm and Robustness.

David Zhang combines subjects such as Amplitude, Image, Image compression, Waveform and Pulse with his study of Algorithm. His work carried out in the field of Feature extraction brings together such families of science as Graph, Feature, Medical imaging, Binary number and Minutiae. His Discriminative model research incorporates elements of Subspace topology, Regularization, Sparse matrix, Sparse approximation and Principal component analysis.

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

Two-dimensional PCA: a new approach to appearance-based face representation and recognition

Jian Yang;D. Zhang;A.F. Frangi;Jing-yu Yang.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2004)

4314 Citations

FSIM: A Feature Similarity Index for Image Quality Assessment

Lin Zhang;Lei Zhang;Xuanqin Mou;D. Zhang.
IEEE Transactions on Image Processing (2011)

2859 Citations

A Completed Modeling of Local Binary Pattern Operator for Texture Classification

Zhenhua Guo;Lei Zhang;David Zhang.
IEEE Transactions on Image Processing (2010)

1938 Citations

Online palmprint identification

D. Zhang;Wai-Kin Kong;J. You;M. Wong.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2003)

1719 Citations

Progressive switching median filter for the removal of impulse noise from highly corrupted images

Zhou Wang;D. Zhang.
IEEE Transactions on Circuits and Systems Ii: Analog and Digital Signal Processing (1999)

1393 Citations

The Visual Object Tracking VOT2017 Challenge Results

Matej Kristan;Ales Leonardis;Jiri Matas;Michael Felsberg.
international conference on computer vision (2017)

1389 Citations

Fisher Discrimination Dictionary Learning for sparse representation

Meng Yang;Lei Zhang;Xiangchu Feng;David Zhang.
international conference on computer vision (2011)

996 Citations

KPCA plus LDA: a complete kernel Fisher discriminant framework for feature extraction and recognition

Jian Yang;A.F. Frangi;Jing-Yu Yang;David Zhang.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2005)

987 Citations

Secure program execution via dynamic information flow tracking

G. Edward Suh;Jae W. Lee;David Zhang;Srinivas Devadas.
architectural support for programming languages and operating systems (2004)

896 Citations

Rotation invariant texture classification using LBP variance (LBPV) with global matching

Zhenhua Guo;Lei Zhang;David Zhang.
Pattern Recognition (2010)

892 Citations

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Best Scientists Citing David Zhang

Yong Xu

Yong Xu

Harbin Institute of Technology

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Lei Zhang

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Hong Kong Polytechnic University

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Nanyang Technological University

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Harbin Institute of Technology

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Nanjing University of Science and Technology

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Northwestern Polytechnical University

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Xiao-Yuan Jing

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Wuhan University

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Zhihui Lai

Shenzhen University

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Ke Gu

Ke Gu

Beijing University of Technology

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Yuan Yan Tang

Yuan Yan Tang

University of Macau

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Dacheng Tao

Dacheng Tao

University of Sydney

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Xinbo Gao

Xinbo Gao

Chongqing University of Posts and Telecommunications

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Licheng Jiao

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Xidian University

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Ahmed Bouridane

Ahmed Bouridane

Northumbria University

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Feiping Nie

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Northwestern Polytechnical University

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Zhao Zhang

Zhao Zhang

Hefei University of Technology

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