H-Index & Metrics Best Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science D-index 123 Citations 70,267 662 World Ranking 40 National Ranking 1

Research.com Recognitions

Awards & Achievements

2020 - ACM Fellow For contributions to visual content understanding techniques and applications

2016 - ACM Distinguished Member

2014 - Fellow of the International Association for Pattern Recognition (IAPR) For contributions to computer vision and pattern recognition

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Machine learning
  • Statistics

Shuicheng Yan mostly deals with Artificial intelligence, Pattern recognition, Feature extraction, Computer vision and Machine learning. His study in Object detection, Convolutional neural network, Facial recognition system, Discriminative model and Image segmentation falls within the category of Artificial intelligence. His study in Pattern recognition is interdisciplinary in nature, drawing from both Contextual image classification and Subspace topology.

His research in Feature extraction intersects with topics in Image processing, Histogram, Visualization, Iterative reconstruction and Robustness. His Computer vision study integrates concerns from other disciplines, such as Representation and Benchmark. His work on Feature as part of general Machine learning study is frequently linked to Context model, therefore connecting diverse disciplines of science.

His most cited work include:

  • Face recognition using Laplacianfaces (2852 citations)
  • Graph Embedding and Extensions: A General Framework for Dimensionality Reduction (2213 citations)
  • Robust Recovery of Subspace Structures by Low-Rank Representation (2079 citations)

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

Shuicheng Yan focuses on Artificial intelligence, Pattern recognition, Computer vision, Machine learning and Feature extraction. All of his Artificial intelligence and Discriminative model, Facial recognition system, Contextual image classification, Image and Face investigations are sub-components of the entire Artificial intelligence study. His studies in Pattern recognition integrate themes in fields like Subspace topology, Feature and Object detection.

His Subspace topology research is multidisciplinary, incorporating perspectives in Linear subspace and Robustness. His Computer vision study frequently links to adjacent areas such as Representation. His work carried out in the field of Machine learning brings together such families of science as Parsing and Benchmark.

He most often published in these fields:

  • Artificial intelligence (73.54%)
  • Pattern recognition (44.05%)
  • Computer vision (21.84%)

What were the highlights of his more recent work (between 2017-2021)?

  • Artificial intelligence (73.54%)
  • Pattern recognition (44.05%)
  • Computer vision (21.84%)

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

His primary areas of study are Artificial intelligence, Pattern recognition, Computer vision, Image and Feature extraction. His Artificial intelligence research focuses on Machine learning and how it connects with Facial recognition system. The study incorporates disciplines such as Feature, Object detection, Representation, Manifold and Robustness in addition to Pattern recognition.

He has included themes like Basis and The Internet in his Computer vision study. His Image study deals with Generative grammar intersecting with Theoretical computer science. While the research belongs to areas of Feature extraction, Shuicheng Yan spends his time largely on the problem of Artificial neural network, intersecting his research to questions surrounding Deep learning.

Between 2017 and 2021, his most popular works were:

  • Scale-Aware Fast R-CNN for Pedestrian Detection (333 citations)
  • Multi-oriented Scene Text Detection via Corner Localization and Region Segmentation (169 citations)
  • Tensor Robust Principal Component Analysis with a New Tensor Nuclear Norm (152 citations)

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

  • Artificial intelligence
  • Machine learning
  • Statistics

Shuicheng Yan spends much of his time researching Artificial intelligence, Pattern recognition, Feature extraction, Computer vision and Image. His is doing research in Segmentation, Pose, Deep learning, Artificial neural network and Convolutional neural network, both of which are found in Artificial intelligence. His biological study focuses on Discriminative model.

He has researched Feature extraction in several fields, including Feature, Pipeline, Representation, Landmark and Key. His study on Face, Facial recognition system, Three-dimensional face recognition and Active appearance model is often connected to Streak as part of broader study in Computer vision. Shuicheng Yan interconnects Visualization, Convolution, Translation and Injective function in the investigation of issues within Image.

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

Face recognition using Laplacianfaces

Xiaofei He;Shuicheng Yan;Yuxiao Hu;P. Niyogi.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2005)

3947 Citations

Graph Embedding and Extensions: A General Framework for Dimensionality Reduction

Shuicheng Yan;Dong Xu;Benyu Zhang;Hong-Jiang Zhang.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2007)

3014 Citations

Network In Network

Min Lin;Qiang Chen;Shuicheng Yan.
arXiv: Neural and Evolutionary Computing (2013)

2489 Citations

Robust Recovery of Subspace Structures by Low-Rank Representation

Guangcan Liu;Zhouchen Lin;Shuicheng Yan;Ju Sun.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2013)

2162 Citations

An HOG-LBP human detector with partial occlusion handling

Xiaoyu Wang;Tony X. Han;Shuicheng Yan.
international conference on computer vision (2009)

2000 Citations

Sparse Representation for Computer Vision and Pattern Recognition

John Wright;Yi Ma;Julien Mairal;Guillermo Sapiro.
Proceedings of the IEEE (2010)

1915 Citations

Neighborhood preserving embedding

Xiaofei He;Deng Cai;Shuicheng Yan;Hong-Jiang Zhang.
international conference on computer vision (2005)

1785 Citations

Visual Classification With Multitask Joint Sparse Representation

Xiao-Tong Yuan;Xiaobai Liu;Shuicheng Yan.
IEEE Transactions on Image Processing (2012)

681 Citations

Learning With $ll ^{1}$ -Graph for Image Analysis

Bin Cheng;Jianchao Yang;Shuicheng Yan;Yun Fu.
IEEE Transactions on Image Processing (2010)

652 Citations

Supervised hashing for image retrieval via image representation learning

Rongkai Xia;Yan Pan;Hanjiang Lai;Cong Liu.
national conference on artificial intelligence (2014)

627 Citations

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Best Scientists Citing Shuicheng Yan

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Ling Shao

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Chinese University of Hong Kong, Shenzhen

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Liang Lin

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Zhouchen Lin

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Jinhui Tang

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