D-Index & Metrics Best Publications
Computer Science
China
2022

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 114 Citations 49,821 591 World Ranking 71 National Ranking 8

Research.com Recognitions

Awards & Achievements

2022 - Research.com Computer Science in China Leader Award

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Quantum mechanics
  • Machine learning

Yi Yang focuses on Artificial intelligence, Pattern recognition, Machine learning, Convolutional neural network and Discriminative model. Artificial intelligence is closely attributed to Computer vision in his study. His work carried out in the field of Pattern recognition brings together such families of science as Object detection, Similarity, Feature and Image retrieval.

His Machine learning research focuses on TRECVID and how it relates to Leverage. As a part of the same scientific family, Yi Yang mostly works in the field of Convolutional neural network, focusing on Training set and, on occasion, Regularization. His Discriminative model research integrates issues from Embedding, Feature learning, Outlier and Pooling.

His most cited work include:

  • Articulated pose estimation with flexible mixtures-of-parts (827 citations)
  • Unlabeled Samples Generated by GAN Improve the Person Re-identification Baseline in Vitro (775 citations)
  • Attention to Scale: Scale-Aware Semantic Image Segmentation (766 citations)

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

Artificial intelligence, Pattern recognition, Optoelectronics, Machine learning and Discriminative model are his primary areas of study. His Artificial intelligence study frequently draws connections between related disciplines such as Computer vision. His work deals with themes such as Laser, Optics and Graphene, which intersect with Optoelectronics.

His Graphene study is focused on Nanotechnology in general.

He most often published in these fields:

  • Artificial intelligence (34.41%)
  • Pattern recognition (14.84%)
  • Optoelectronics (14.77%)

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

  • Artificial intelligence (34.41%)
  • Pattern recognition (14.84%)
  • Machine learning (12.29%)

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

The scientist’s investigation covers issues in Artificial intelligence, Pattern recognition, Machine learning, Discriminative model and Segmentation. His Artificial intelligence research is multidisciplinary, incorporating elements of Domain, Computer vision and Code. Yi Yang has researched Pattern recognition in several fields, including Object detection and Representation.

His Machine learning study which covers Graph that intersects with Graph. His research is interdisciplinary, bridging the disciplines of Feature learning and Discriminative model. His studies deal with areas such as Object and Embedding as well as Feature.

Between 2019 and 2021, his most popular works were:

  • Random Erasing Data Augmentation (214 citations)
  • NAS-Bench-201: Extending the Scope of Reproducible Neural Architecture Search (90 citations)
  • Deep Unfolded Robust PCA With Application to Clutter Suppression in Ultrasound (49 citations)

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

  • Artificial intelligence
  • Quantum mechanics
  • Machine learning

His main research concerns Artificial intelligence, Pattern recognition, Machine learning, Discriminative model and Segmentation. Yi Yang has included themes like Domain and Code in his Artificial intelligence study. His research in Pattern recognition tackles topics such as Process which are related to areas like Ground truth and Benchmark.

His Machine learning study combines topics in areas such as Adversarial system, Graph and Task. His Discriminative model research incorporates themes from Parsing, Representation and Feature learning. As a member of one scientific family, Yi Yang mostly works in the field of Convolutional neural network, focusing on Contextual image classification and, on occasion, Object detection and Pruning.

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

Articulated pose estimation with flexible mixtures-of-parts

Yi Yang;Deva Ramanan.
computer vision and pattern recognition (2011)

1229 Citations

Deep Captioning with Multimodal Recurrent Neural Networks (m-RNN)

Junhua Mao;Junhua Mao;Wei Xu;Yi Yang;Jiang Wang.
international conference on learning representations (2015)

686 Citations

Person Re-identification: Past, Present and Future

Liang Zheng;Yi Yang;Alexander G. Hauptmann.
arXiv: Computer Vision and Pattern Recognition (2016)

673 Citations

Articulated Human Detection with Flexible Mixtures of Parts

Yi Yang;Deva Ramanan.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2013)

670 Citations

Attention to Scale: Scale-Aware Semantic Image Segmentation

Liang-Chieh Chen;Yi Yang;Jiang Wang;Wei Xu.
computer vision and pattern recognition (2016)

621 Citations

Unlabeled Samples Generated by GAN Improve the Person Re-identification Baseline in Vitro

Zhedong Zheng;Liang Zheng;Yi Yang.
international conference on computer vision (2017)

620 Citations

l 2,1 -norm regularized discriminative feature selection for unsupervised learning

Yi Yang;Heng Tao Shen;Zhigang Ma;Zi Huang.
international joint conference on artificial intelligence (2011)

585 Citations

Random Erasing Data Augmentation

Zhun Zhong;Liang Zheng;Guoliang Kang;Shaozi Li.
arXiv: Computer Vision and Pattern Recognition (2017)

579 Citations

L2,1-Norm Regularized Discriminative Feature Selection for Unsupervised

Yi Yang;Heng Tao Shen;Zhigang Ma;Zi Huang.
international joint conference on artificial intelligence (2011)

572 Citations

Beyond Part Models: Person Retrieval with Refined Part Pooling (and a Strong Convolutional Baseline)

Yifan Sun;Liang Zheng;Yi Yang;Qi Tian.
european conference on computer vision (2018)

552 Citations

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

Contact us

Best Scientists Citing Yi Yang

Qi Tian

Qi Tian

Huawei Technologies (China)

Publications: 143

Xuelong Li

Xuelong Li

Northwestern Polytechnical University

Publications: 125

Dacheng Tao

Dacheng Tao

University of Sydney

Publications: 109

Shuicheng Yan

Shuicheng Yan

National University of Singapore

Publications: 102

Meng Wang

Meng Wang

Hefei University of Technology

Publications: 95

Heng Tao Shen

Heng Tao Shen

University of Electronic Science and Technology of China

Publications: 89

Yang Yang

Yang Yang

University of Electronic Science and Technology of China

Publications: 88

Feiping Nie

Feiping Nie

Northwestern Polytechnical University

Publications: 85

Xiaogang Wang

Xiaogang Wang

Chinese University of Hong Kong

Publications: 83

Chunhua Shen

Chunhua Shen

Zhejiang University

Publications: 74

Liang Lin

Liang Lin

Sun Yat-sen University

Publications: 71

Alan L. Yuille

Alan L. Yuille

Johns Hopkins University

Publications: 70

Fumin Shen

Fumin Shen

University of Electronic Science and Technology of China

Publications: 68

Tao Mei

Tao Mei

Jingdong (China)

Publications: 67

Richang Hong

Richang Hong

Hefei University of Technology

Publications: 66

Nicu Sebe

Nicu Sebe

University of Trento

Publications: 65

Trending Scientists

Richard A. Bettis

Richard A. Bettis

University of North Carolina at Chapel Hill

Eduardo Engel

Eduardo Engel

University of Chile

Giangiacomo Minak

Giangiacomo Minak

University of Bologna

Mark A. Burns

Mark A. Burns

University of Michigan–Ann Arbor

Michael Marsch

Michael Marsch

Philipp University of Marburg

Jeong-Woo Choi

Jeong-Woo Choi

Sogang University

Robert E. Ferrell

Robert E. Ferrell

University of Pittsburgh

Robin R. Gutell

Robin R. Gutell

The University of Texas at Austin

Martin Melles

Martin Melles

University of Cologne

Qingfei Wang

Qingfei Wang

China University of Geosciences

Thomas W. Farmer

Thomas W. Farmer

William & Mary

Steve Sussman

Steve Sussman

University of Southern California

Ian C. K. Wong

Ian C. K. Wong

University College London

Arthur M. Feldman

Arthur M. Feldman

Thomas Jefferson University

Martyn J. Parker

Martyn J. Parker

Peterborough City Hospital

Richard J. Wainscoat

Richard J. Wainscoat

University of Hawaii System

Something went wrong. Please try again later.