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 61 Citations 16,381 323 World Ranking 1468 National Ranking 820

Research.com Recognitions

Awards & Achievements

2018 - Fellow of the International Association for Pattern Recognition (IAPR) For contributions to human action and gesture analysis

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Computer vision
  • Machine learning

Junsong Yuan mainly focuses on Artificial intelligence, Computer vision, Pattern recognition, Feature extraction and Discriminative model. In his study, Branch and bound is inextricably linked to Machine learning, which falls within the broad field of Artificial intelligence. His study explores the link between Computer vision and topics such as Detector that cross with problems in Dynamic programming and Scale.

His work carried out in the field of Pattern recognition brings together such families of science as Feature, Image and Selection. His Feature extraction research is multidisciplinary, incorporating perspectives in Salient, Data mining, Curse of dimensionality, Hidden Markov model and Phrase. His Discriminative model study combines topics from a wide range of disciplines, such as Object, Cognitive neuroscience of visual object recognition, Spectral clustering, Categorization and Boosting.

His most cited work include:

  • Mining actionlet ensemble for action recognition with depth cameras (1170 citations)
  • Sparse reconstruction cost for abnormal event detection (552 citations)
  • Robust Part-Based Hand Gesture Recognition Using Kinect Sensor (491 citations)

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

His primary areas of study are Artificial intelligence, Pattern recognition, Computer vision, Discriminative model and Machine learning. His study involves Feature extraction, Object, Pose, Object detection and Segmentation, a branch of Artificial intelligence. Feature extraction is closely attributed to Visualization in his research.

His Pattern recognition study incorporates themes from Pixel, Feature and Benchmark. His Robustness research extends to Computer vision, which is thematically connected. His Discriminative model research includes elements of Mutual information and Leverage.

He most often published in these fields:

  • Artificial intelligence (82.32%)
  • Pattern recognition (43.27%)
  • Computer vision (36.94%)

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

  • Artificial intelligence (82.32%)
  • Pattern recognition (43.27%)
  • Computer vision (36.94%)

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

Artificial intelligence, Pattern recognition, Computer vision, Machine learning and Object are his primary areas of study. His is involved in several facets of Artificial intelligence study, as is seen by his studies on Pose, Discriminative model, Convolutional neural network, Leverage and RGB color model. His research integrates issues of Object detection, Autoencoder and Benchmark in his study of Pattern recognition.

The study incorporates disciplines such as Frame and Reliability in addition to Computer vision. His Categorical variable study, which is part of a larger body of work in Machine learning, is frequently linked to Selection, bridging the gap between disciplines. His studies in Object integrate themes in fields like Margin, Construct and Segmentation.

Between 2019 and 2021, his most popular works were:

  • Temporal-Context Enhanced Detection of Heavily Occluded Pedestrians (13 citations)
  • Measuring Generalisation to Unseen Viewpoints, Articulations, Shapes and Objects for 3D Hand Pose Estimation under Hand-Object Interaction (9 citations)
  • Learning progressive joint propagation for human motion prediction (9 citations)

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

  • Artificial intelligence
  • Computer vision
  • Machine learning

Junsong Yuan mainly investigates Artificial intelligence, Pattern recognition, Computer vision, RGB color model and Machine learning. By researching both Artificial intelligence and Selection, he produces research that crosses academic boundaries. His work in the fields of Feature learning, Convolutional neural network and Anomaly detection overlaps with other areas such as Action recognition.

His biological study deals with issues like Information extraction, which deal with fields such as Discriminative model and Benchmark. His work on Feature and Human motion as part of general Computer vision study is frequently linked to Pedestrian detection and Joint, therefore connecting diverse disciplines of science. His Machine learning research incorporates themes from Focus and Sequence.

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

Mining actionlet ensemble for action recognition with depth cameras

Jiang Wang;Zicheng Liu;Ying Wu;Junsong Yuan.
computer vision and pattern recognition (2012)

1555 Citations

Sparse reconstruction cost for abnormal event detection

Yang Cong;Junsong Yuan;Ji Liu.
computer vision and pattern recognition (2011)

737 Citations

Robust Part-Based Hand Gesture Recognition Using Kinect Sensor

Zhou Ren;Junsong Yuan;Jingjing Meng;Zhengyou Zhang.
IEEE Transactions on Multimedia (2013)

678 Citations

Robust hand gesture recognition based on finger-earth mover's distance with a commodity depth camera

Zhou Ren;Junsong Yuan;Zhengyou Zhang.
acm multimedia (2011)

503 Citations

Learning Actionlet Ensemble for 3D Human Action Recognition

Jiang Wang;Zicheng Liu;Ying Wu;Junsong Yuan.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2014)

464 Citations

Discriminative subvolume search for efficient action detection

Junsong Yuan;Zicheng Liu;Ying Wu.
computer vision and pattern recognition (2009)

369 Citations

Robust hand gesture recognition with kinect sensor

Zhou Ren;Jingjing Meng;Junsong Yuan;Zhengyou Zhang.
acm multimedia (2011)

360 Citations

Discovery of Collocation Patterns: from Visual Words to Visual Phrases

Junsong Yuan;Ying Wu;Ming Yang.
computer vision and pattern recognition (2007)

315 Citations

Abnormal event detection in crowded scenes using sparse representation

Yang Cong;Junsong Yuan;Ji Liu.
Pattern Recognition (2013)

289 Citations

Towards Scalable Summarization of Consumer Videos Via Sparse Dictionary Selection

Yang Cong;Junsong Yuan;Jiebo Luo.
IEEE Transactions on Multimedia (2012)

257 Citations

Best Scientists Citing Junsong Yuan

Qi Tian

Qi Tian

Huawei Technologies (China)

Publications: 44

Rongrong Ji

Rongrong Ji

Xiamen University

Publications: 44

Dacheng Tao

Dacheng Tao

University of Sydney

Publications: 38

Tae-Kyun Kim

Tae-Kyun Kim

Imperial College London

Publications: 38

Ling Shao

Ling Shao

Inception Institute of Artificial Intelligence

Publications: 37

Yun Fu

Yun Fu

Northeastern University

Publications: 37

Xuelong Li

Xuelong Li

Northwestern Polytechnical University

Publications: 34

Wanqing Li

Wanqing Li

University of Wollongong

Publications: 34

Ling-Yu Duan

Ling-Yu Duan

Peking University

Publications: 31

Hongxun Yao

Hongxun Yao

Harbin Institute of Technology

Publications: 29

Qingming Huang

Qingming Huang

Chinese Academy of Sciences

Publications: 28

Wen Gao

Wen Gao

Peking University

Publications: 27

Zicheng Liu

Zicheng Liu

Huazhong University of Science and Technology

Publications: 27

Jiwen Lu

Jiwen Lu

Tsinghua University

Publications: 27

Jiebo Luo

Jiebo Luo

University of Rochester

Publications: 24

Gang Wang

Gang Wang

Alibaba Group (China)

Publications: 24

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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