H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 65 Citations 30,603 310 World Ranking 1144 National Ranking 107

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Computer vision
  • Machine learning

His primary areas of investigation include Artificial intelligence, Pattern recognition, Machine learning, Discriminative model and Convolutional neural network. His studies link Computer vision with Artificial intelligence. In general Pattern recognition, his work in Normalization is often linked to Action recognition linking many areas of study.

His Machine learning research includes themes of Context, Structure, Key and Process. His Discriminative model research incorporates themes from Artificial neural network and Data mining. His Convolutional neural network study combines topics in areas such as Facial recognition system, Confusion matrix, Multi resolution and Knowledge engineering.

His most cited work include:

  • Joint Face Detection and Alignment Using Multitask Cascaded Convolutional Networks (2105 citations)
  • A Discriminative Feature Learning Approach for Deep Face Recognition (1894 citations)
  • Temporal Segment Networks: Towards Good Practices for Deep Action Recognition (1578 citations)

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

His scientific interests lie mostly in Artificial intelligence, Pattern recognition, Computer vision, Machine learning and Convolutional neural network. His work in Image, Deep learning, Discriminative model, Feature extraction and Feature are all subfields of Artificial intelligence research. His research ties Feature and Discriminative model together.

Yu Qiao has included themes like Facial recognition system, Face, Speech recognition and Representation in his Pattern recognition study. His study on Computer vision is mostly dedicated to connecting different topics, such as Feature vector. Margin and Transfer of learning are subfields of Machine learning in which his conducts study.

He most often published in these fields:

  • Artificial intelligence (73.62%)
  • Pattern recognition (40.75%)
  • Computer vision (24.61%)

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

  • Artificial intelligence (73.62%)
  • Pattern recognition (40.75%)
  • Computer vision (24.61%)

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

Yu Qiao mostly deals with Artificial intelligence, Pattern recognition, Computer vision, Image and Machine learning. His biological study deals with issues like Code, which deal with fields such as Object. He has researched Pattern recognition in several fields, including Representation, Feature and Facial expression.

His work deals with themes such as Graph and Graph, which intersect with Computer vision. In general Image study, his work on Superresolution often relates to the realm of Process, thereby connecting several areas of interest. The concepts of his Machine learning study are interwoven with issues in Object detection and Detector.

Between 2019 and 2021, his most popular works were:

  • Region Attention Networks for Pose and Occlusion Robust Facial Expression Recognition (65 citations)
  • Suppressing Uncertainties for Large-Scale Facial Expression Recognition (28 citations)
  • Fabricating better metal-organic frameworks separators for Li–S batteries: Pore sizes effects inspired channel modification strategy (22 citations)

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

  • Artificial intelligence
  • Computer vision
  • Machine learning

Yu Qiao spends much of his time researching Artificial intelligence, Pattern recognition, Chemical engineering, Computer vision and Image. His biological study spans a wide range of topics, including Machine learning and Generalization. His work on Feature extraction as part of general Pattern recognition study is frequently linked to Domain, bridging the gap between disciplines.

His study in the field of Pyrolysis also crosses realms of Lower temperature. The study incorporates disciplines such as Focus and Interpolation in addition to Computer vision. His Image research includes elements of Artificial neural network and Noisy data.

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.

Top Publications

Joint Face Detection and Alignment Using Multitask Cascaded Convolutional Networks

Kaipeng Zhang;Zhanpeng Zhang;Zhifeng Li;Yu Qiao.
IEEE Signal Processing Letters (2016)

2577 Citations

A Discriminative Feature Learning Approach for Deep Face Recognition

Yandong Wen;Kaipeng Zhang;Zhifeng Li;Yu Qiao.
european conference on computer vision (2016)

2264 Citations

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

Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks

Kaipeng Zhang;Zhanpeng Zhang;Zhifeng Li;Yu Qiao.
arXiv: Computer Vision and Pattern Recognition (2016)

1255 Citations

Action recognition with trajectory-pooled deep-convolutional descriptors

Limin Wang;Yu Qiao;Xiaoou Tang.
computer vision and pattern recognition (2015)

984 Citations

Bag of visual words and fusion methods for action recognition

Xiaojiang Peng;Limin Wang;Xingxing Wang;Yu Qiao.
Computer Vision and Image Understanding (2016)

712 Citations

Detecting Text in Natural Image with Connectionist Text Proposal Network

Zhi Tian;Weilin Huang;Weilin Huang;Tong He;Pan He.
european conference on computer vision (2016)

615 Citations

ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks

Xintao Wang;Ke Yu;Shixiang Wu;Jinjin Gu.
european conference on computer vision (2018)

520 Citations

NTIRE 2017 Challenge on Single Image Super-Resolution: Methods and Results

Radu Timofte;Eirikur Agustsson;Luc Van Gool;Ming-Hsuan Yang.
computer vision and pattern recognition (2017)

491 Citations

Status of trace element emission in a coal combustion process: a review

Minghou Xu;Rong Yan;Chuguang Zheng;Yu Qiao.
Fuel Processing Technology (2004)

465 Citations

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking h-index is inferred from publications deemed to belong to the considered discipline.

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Top Scientists Citing Yu Qiao

Radu Timofte

Radu Timofte

ETH Zurich

Publications: 80

Chunhua Shen

Chunhua Shen

University of Adelaide

Publications: 60

Luc Van Gool

Luc Van Gool

ETH Zurich

Publications: 55

Xiang Bai

Xiang Bai

Huazhong University of Science and Technology

Publications: 54

Minghou Xu

Minghou Xu

Huazhong University of Science and Technology

Publications: 46

Larry S. Davis

Larry S. Davis

University of Maryland, College Park

Publications: 44

Jiashi Feng

Jiashi Feng

National University of Singapore

Publications: 43

Liang Lin

Liang Lin

Sun Yat-sen University

Publications: 42

Ling Shao

Ling Shao

Inception Institute of Artificial Intelligence

Publications: 42

Lianwen Jin

Lianwen Jin

South China University of Technology

Publications: 41

Dahua Lin

Dahua Lin

Chinese University of Hong Kong

Publications: 40

Dacheng Tao

Dacheng Tao

University of Sydney

Publications: 39

Yun Fu

Yun Fu

Northeastern University

Publications: 39

Jiwen Lu

Jiwen Lu

Tsinghua University

Publications: 39

Weihong Deng

Weihong Deng

Beijing University of Posts and Telecommunications

Publications: 38

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