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 52 Citations 11,760 275 World Ranking 2609 National Ranking 1383

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Statistics
  • Machine learning

His scientific interests lie mostly in Artificial intelligence, Pattern recognition, Computer vision, Algorithm and Discriminative model. His work in Compressed sensing, Convolutional neural network, Cluster analysis, Feature selection and Multispectral image is related to Artificial intelligence. His Pattern recognition study integrates concerns from other disciplines, such as Histogram and Facial recognition system.

His Computer vision research is multidisciplinary, incorporating elements of Subspace topology, Mr imaging and Mr images. His study in the fields of Regularization under the domain of Algorithm overlaps with other disciplines such as Degradation, Speedup and Bottleneck. His work deals with themes such as Feature learning and Categorization, which intersect with Discriminative model.

His most cited work include:

  • Robust tracking using local sparse appearance model and K-selection (437 citations)
  • The Benefit of Group Sparsity (355 citations)
  • Learning with Structured Sparsity (307 citations)

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

Junzhou Huang mostly deals with Artificial intelligence, Pattern recognition, Computer vision, Machine learning and Theoretical computer science. His Artificial intelligence study focuses mostly on Deep learning, Segmentation, Image, Feature extraction and Image segmentation. His research in Pattern recognition intersects with topics in Feature and Compressed sensing.

Junzhou Huang interconnects Generalization and Representation in the investigation of issues within Machine learning. The concepts of his Theoretical computer science study are interwoven with issues in Feature learning and Graph. His study in Graph is interdisciplinary in nature, drawing from both Embedding and Graph.

He most often published in these fields:

  • Artificial intelligence (61.50%)
  • Pattern recognition (26.87%)
  • Computer vision (19.11%)

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

  • Artificial intelligence (61.50%)
  • Machine learning (19.39%)
  • Theoretical computer science (14.96%)

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

Junzhou Huang mainly investigates Artificial intelligence, Machine learning, Theoretical computer science, Graph and Graph. His studies link Pattern recognition with Artificial intelligence. His Pattern recognition research is multidisciplinary, incorporating perspectives in Modality and Medical imaging.

His Machine learning research focuses on subjects like Annotation, which are linked to Liver segmentation. His Graph research is multidisciplinary, relying on both Artificial neural network, Recurrent neural network, Algorithm and Message passing. His studies deal with areas such as Adversarial system and Embedding as well as Graph.

Between 2019 and 2021, his most popular works were:

  • DropEdge: Towards Deep Graph Convolutional Networks on Node Classification (109 citations)
  • Early triage of critically ill COVID-19 patients using deep learning (55 citations)
  • Graph Representation Learning via Graphical Mutual Information Maximization (34 citations)

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

  • Artificial intelligence
  • Machine learning
  • Statistics

Junzhou Huang focuses on Artificial intelligence, Graph, Theoretical computer science, Machine learning and Graph. His Artificial intelligence research includes themes of Sample, Adaptation and Pattern recognition. Segmentation is closely connected to Translation in his research, which is encompassed under the umbrella topic of Pattern recognition.

The study incorporates disciplines such as Autoencoder, Clustering coefficient, Taylor series and Computation in addition to Theoretical computer science. Junzhou Huang combines subjects such as Cover and Face with his study of Machine learning. His Graph embedding study in the realm of Graph interacts with subjects such as Rumor.

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

Robust tracking using local sparse appearance model and K-selection

Baiyang Liu;Junzhou Huang;Lin Yang;Casimir Kulikowsk.
computer vision and pattern recognition (2011)

578 Citations

The Benefit of Group Sparsity

Junzhou Huang;Tong Zhang.
Annals of Statistics (2010)

492 Citations

Learning with Structured Sparsity

Junzhou Huang;Tong Zhang;Dimitris Metaxas.
Journal of Machine Learning Research (2011)

345 Citations

Learning active facial patches for expression analysis

Lin Zhong;Qingshan Liu;Peng Yang;Bo Liu.
computer vision and pattern recognition (2012)

305 Citations

Efficient MR image reconstruction for compressed MR imaging

Junzhou Huang;Shaoting Zhang;Dimitris N. Metaxas.
Medical Image Analysis (2011)

301 Citations

Robust and fast collaborative tracking with two stage sparse optimization

Baiyang Liu;Lin Yang;Junzhou Huang;Peter Meer.
european conference on computer vision (2010)

276 Citations

Pose-Free Facial Landmark Fitting via Optimized Part Mixtures and Cascaded Deformable Shape Model

Xiang Yu;Junzhou Huang;Shaoting Zhang;Wang Yan.
international conference on computer vision (2013)

270 Citations

Automatic image annotation using group sparsity

Shaoting Zhang;Junzhou Huang;Yuchi Huang;Yang Yu.
computer vision and pattern recognition (2010)

236 Citations

Discrimination-aware channel pruning for deep neural networks

Zhuangwei Zhuang;Mingkui Tan;Bohan Zhuang;Jing Liu.
neural information processing systems (2018)

196 Citations

Large-scale multi-view spectral clustering via bipartite graph

Yeqing Li;Feiping Nie;Heng Huang;Junzhou Huang.
national conference on artificial intelligence (2015)

194 Citations

Best Scientists Citing Junzhou Huang

Dimitris N. Metaxas

Dimitris N. Metaxas

Rutgers, The State University of New Jersey

Publications: 66

Shaoting Zhang

Shaoting Zhang

University of Electronic Science and Technology of China

Publications: 45

Mingkui Tan

Mingkui Tan

South China University of Technology

Publications: 39

Dacheng Tao

Dacheng Tao

University of Sydney

Publications: 37

Francis Bach

Francis Bach

French Institute for Research in Computer Science and Automation - INRIA

Publications: 33

Xuelong Li

Xuelong Li

Northwestern Polytechnical University

Publications: 32

Feiping Nie

Feiping Nie

Northwestern Polytechnical University

Publications: 31

Qi Tian

Qi Tian

Huawei Technologies (China)

Publications: 30

Ming-Hsuan Yang

Ming-Hsuan Yang

University of California, Merced

Publications: 30

Yi Yang

Yi Yang

Zhejiang University

Publications: 29

Lei Zhang

Lei Zhang

Hong Kong Polytechnic University

Publications: 25

Huchuan Lu

Huchuan Lu

Dalian University of Technology

Publications: 25

Xi Peng

Xi Peng

Sichuan University

Publications: 24

Yue Huang

Yue Huang

Xiamen University

Publications: 24

Bernard Ghanem

Bernard Ghanem

King Abdullah University of Science and Technology

Publications: 23

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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