H-Index & Metrics Best Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science D-index 55 Citations 16,297 161 World Ranking 2187 National Ranking 219

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Machine learning
  • Computer vision

His primary scientific interests are in Artificial intelligence, Pattern recognition, Machine learning, Object detection and Structure. Visualization, Feature extraction, Categorization, Discriminative model and Parsing are among the areas of Artificial intelligence where he concentrates his study. His study in Discriminative model is interdisciplinary in nature, drawing from both Artificial neural network, Supervised learning and Training set.

His biological study spans a wide range of topics, including Contextual image classification, Facial recognition system, Generative model and RGB color model. His work deals with themes such as Viola–Jones object detection framework and Closed captioning, which intersect with Machine learning. His Object detection research is multidisciplinary, incorporating elements of Pyramid, Segmentation, Software engineering and Pyramid.

His most cited work include:

  • Temporal Segment Networks: Towards Good Practices for Deep Action Recognition (1578 citations)
  • Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognition (589 citations)
  • Unsupervised Feature Learning via Non-parametric Instance Discrimination (552 citations)

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

His primary areas of investigation include Artificial intelligence, Pattern recognition, Machine learning, Computer vision and Object detection. Dahua Lin works mostly in the field of Artificial intelligence, limiting it down to topics relating to Natural language processing and, in certain cases, Closed captioning. His work in the fields of Pattern recognition, such as Discriminative model and Feature extraction, overlaps with other areas such as Structure.

His research in the fields of Feature and Deep learning overlaps with other disciplines such as Sampling and Generalization. Dahua Lin combines subjects such as Representation and Leverage with his study of Computer vision. His study looks at the intersection of Segmentation and topics like Inpainting with Upsampling.

He most often published in these fields:

  • Artificial intelligence (72.61%)
  • Pattern recognition (23.24%)
  • Machine learning (21.16%)

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

  • Artificial intelligence (72.61%)
  • Computer vision (16.60%)
  • Pattern recognition (23.24%)

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

Dahua Lin spends much of his time researching Artificial intelligence, Computer vision, Pattern recognition, Feature and Machine learning. All of his Artificial intelligence and Object detection, Image, Parsing, Pyramid and Leverage investigations are sub-components of the entire Artificial intelligence study. His work is dedicated to discovering how Object detection, Pyramid are connected with Noise and other disciplines.

His work on Object, Monocular and Point cloud as part of general Computer vision research is frequently linked to Electronic equipment and Storytelling, bridging the gap between disciplines. His Pattern recognition research integrates issues from Regularization and Graph. His studies deal with areas such as Domain and Outlier as well as Machine learning.

Between 2019 and 2021, his most popular works were:

  • Temporal Action Detection with Structured Segment Networks (43 citations)
  • When NAS Meets Robustness: In Search of Robust Architectures Against Adversarial Attacks (31 citations)
  • Prime Sample Attention in Object Detection (29 citations)

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

  • Artificial intelligence
  • Machine learning
  • Computer vision

Dahua Lin mostly deals with Artificial intelligence, Computer vision, Machine learning, Pattern recognition and Object detection. Dahua Lin has included themes like Task analysis and Natural language processing in his Artificial intelligence study. The various areas that Dahua Lin examines in his Computer vision study include Binaural recording and Representation.

Dahua Lin merges Machine learning with Generalization in his study. His Pattern recognition research incorporates themes from Pyramid and Regularization. His Object detection research is multidisciplinary, relying on both Minimum bounding box and Task.

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

Temporal Segment Networks: Towards Good Practices for Deep Action Recognition

Limin Wang;Yuanjun Xiong;Zhe Wang;Yu Qiao.
european conference on computer vision (2016)

1376 Citations

Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognition

Sijie Yan;Yuanjun Xiong;Dahua Lin.
national conference on artificial intelligence (2018)

673 Citations

Unsupervised Feature Learning via Non-parametric Instance Discrimination

Zhirong Wu;Yuanjun Xiong;Stella X. Yu;Dahua Lin.
computer vision and pattern recognition (2018)

603 Citations

MMDetection: Open MMLab Detection Toolbox and Benchmark.

Kai Chen;Jiaqi Wang;Jiangmiao Pang;Yuhang Cao.
arXiv: Computer Vision and Pattern Recognition (2019)

424 Citations

PSANet: Point-wise Spatial Attention Network for Scene Parsing

Hengshuang Zhao;Yi Zhang;Shu Liu;Jianping Shi.
european conference on computer vision (2018)

355 Citations

Temporal Action Detection with Structured Segment Networks

Yue Zhao;Yuanjun Xiong;Yuanjun Xiong;Limin Wang;Zhirong Wu;Zhirong Wu.
international conference on computer vision (2017)

341 Citations

Hybrid Task Cascade for Instance Segmentation

Kai Chen;Wanli Ouyang;Chen Change Loy;Dahua Lin.
computer vision and pattern recognition (2019)

321 Citations

Holistic Scene Understanding for 3D Object Detection with RGBD Cameras

Dahua Lin;Sanja Fidler;Raquel Urtasun.
international conference on computer vision (2013)

265 Citations

Libra R-CNN: Towards Balanced Learning for Object Detection

Jiangmiao Pang;Kai Chen;Jianping Shi;Huajun Feng.
computer vision and pattern recognition (2019)

258 Citations

Detecting Visual Relationships with Deep Relational Networks

Bo Dai;Yuqi Zhang;Dahua Lin.
computer vision and pattern recognition (2017)

248 Citations

If you think any of the details on this page are incorrect, let us know.

Contact us

Best Scientists Citing Dahua Lin

Michael S. Strano

Michael S. Strano

MIT

Publications: 57

Larry S. Davis

Larry S. Davis

University of Maryland, College Park

Publications: 51

Xiaogang Wang

Xiaogang Wang

Chinese University of Hong Kong

Publications: 47

Dacheng Tao

Dacheng Tao

University of Sydney

Publications: 43

Qi Tian

Qi Tian

Huawei Technologies (China)

Publications: 42

Luc Van Gool

Luc Van Gool

ETH Zurich

Publications: 41

Tao Mei

Tao Mei

Jingdong (China)

Publications: 41

Xiaoou Tang

Xiaoou Tang

Chinese University of Hong Kong

Publications: 40

Yu Qiao

Yu Qiao

Chinese Academy of Sciences

Publications: 40

Wanli Ouyang

Wanli Ouyang

University of Sydney

Publications: 38

Chunhua Shen

Chunhua Shen

University of Adelaide

Publications: 38

Trevor Darrell

Trevor Darrell

University of California, Berkeley

Publications: 38

Jiashi Feng

Jiashi Feng

National University of Singapore

Publications: 37

Andrew Zisserman

Andrew Zisserman

University of Oxford

Publications: 36

Chuang Gan

Chuang Gan

IBM (United States)

Publications: 36

Wei Liu

Wei Liu

Tencent (China)

Publications: 35

Something went wrong. Please try again later.