H-Index & Metrics Best Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science D-index 34 Citations 7,075 168 World Ranking 6414 National Ranking 41

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Computer vision
  • Machine learning

His main research concerns Artificial intelligence, Pattern recognition, Computer vision, Machine learning and Object detection. His research on Artificial intelligence often connects related areas such as Ranking. His Pattern recognition research incorporates themes from Cognitive neuroscience of visual object recognition, M-estimator, Image processing, Hierarchical clustering and Affinity propagation.

His work on Image resolution, Stereoscopy, Stereo camera and Orientation as part of his general Computer vision study is frequently connected to Common point, thereby bridging the divide between different branches of science. His work is dedicated to discovering how Object detection, Pixel are connected with Hierarchy and Segmentation and other disciplines. His Image retrieval research is multidisciplinary, incorporating elements of Artificial neural network, Hash function, Deep learning and Convolutional neural network.

His most cited work include:

  • Deep learning of binary hash codes for fast image retrieval (400 citations)
  • RANSAC-based DARCES: a new approach to fast automatic registration of partially overlapping range images (310 citations)
  • Ordinal hyperplanes ranker with cost sensitivities for age estimation (252 citations)

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

Chu-Song Chen spends much of his time researching Artificial intelligence, Computer vision, Pattern recognition, Feature extraction and Machine learning. His study involves Object detection, Facial recognition system, Deep learning, Video tracking and Contextual image classification, a branch of Artificial intelligence. The Facial recognition system study combines topics in areas such as Subspace topology and Speech recognition.

His work carried out in the field of Deep learning brings together such families of science as Artificial neural network and Image retrieval. His Computer vision study typically links adjacent topics like Computer graphics. His Pattern recognition study integrates concerns from other disciplines, such as Histogram, Cognitive neuroscience of visual object recognition and Invariant.

He most often published in these fields:

  • Artificial intelligence (92.68%)
  • Computer vision (53.17%)
  • Pattern recognition (40.00%)

What were the highlights of his more recent work (between 2015-2021)?

  • Artificial intelligence (92.68%)
  • Deep learning (11.71%)
  • Pattern recognition (40.00%)

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

His scientific interests lie mostly in Artificial intelligence, Deep learning, Pattern recognition, Artificial neural network and Machine learning. His Artificial intelligence research focuses on Computer vision and how it connects with Model compression. His research in Deep learning tackles topics such as Facial expression which are related to areas like Transfer of learning and Ordinal regression.

When carried out as part of a general Pattern recognition research project, his work on Classifier is frequently linked to work in Daytime, therefore connecting diverse disciplines of study. His Machine learning research incorporates elements of Facial recognition system, Feature extraction, Key and Conditional random field. His research in the fields of Visual Word overlaps with other disciplines such as Binary code.

Between 2015 and 2021, his most popular works were:

  • Learning Compact Binary Descriptors with Unsupervised Deep Neural Networks (225 citations)
  • Supervised Learning of Semantics-Preserving Hash via Deep Convolutional Neural Networks (181 citations)
  • MVC: A Dataset for View-Invariant Clothing Retrieval and Attribute Prediction (42 citations)

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

  • Artificial intelligence
  • Computer vision
  • Machine learning

His primary scientific interests are in Artificial intelligence, Deep learning, Machine learning, Pattern recognition and Artificial neural network. His research integrates issues of Information retrieval and Computer vision in his study of Artificial intelligence. His study looks at the relationship between Deep learning and fields such as Facial expression, as well as how they intersect with chemical problems.

He combines subjects such as Contextual image classification, Multimedia search and Visual Word with his study of Machine learning. His Pattern recognition study frequently links to related topics such as Image retrieval. Chu-Song Chen interconnects Object detection, Hash function, Quantization and Feature in the investigation of issues within Image retrieval.

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

Deep learning of binary hash codes for fast image retrieval

Kevin Lin;Huei-Fang Yang;Jen-Hao Hsiao;Chu-Song Chen.
computer vision and pattern recognition (2015)

530 Citations

RANSAC-based DARCES: a new approach to fast automatic registration of partially overlapping range images

Chu-Song Chen;Yi-Ping Hung;Jen-Bo Cheng.
IEEE Transactions on Pattern Analysis and Machine Intelligence (1999)

453 Citations

Ordinal hyperplanes ranker with cost sensitivities for age estimation

Kuang-Yu Chang;Chu-Song Chen;Yi-Ping Hung.
computer vision and pattern recognition (2011)

349 Citations

Multiple Kernel Fuzzy Clustering

Hsin-Chien Huang;Yung-Yu Chuang;Chu-Song Chen.
IEEE Transactions on Fuzzy Systems (2012)

316 Citations

Cross-Age Reference Coding for Age-Invariant Face Recognition and Retrieval

Bor-Chun Chen;Chu-Song Chen;Winston H. Hsu.
european conference on computer vision (2014)

302 Citations

Learning Compact Binary Descriptors with Unsupervised Deep Neural Networks

Kevin Lin;Jiwen Lu;Chu-Song Chen;Jie Zhou.
computer vision and pattern recognition (2016)

257 Citations

Supervised Learning of Semantics-Preserving Hash via Deep Convolutional Neural Networks

Huei-Fang Yang;Kevin Lin;Chu-Song Chen.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2018)

227 Citations

Face Recognition and Retrieval Using Cross-Age Reference Coding With Cross-Age Celebrity Dataset

Bor-Chun Chen;Chu-Song Chen;Winston H. Hsu.
IEEE Transactions on Multimedia (2015)

207 Citations

Efficient hierarchical method for background subtraction

Yu-Ting Chen;Chu-Song Chen;Chun-Rong Huang;Yi-Ping Hung.
Pattern Recognition (2007)

187 Citations

Moving cast shadow detection using physics-based features

Jia-Bin Huang;Chu-Song Chen.
computer vision and pattern recognition (2009)

172 Citations

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Best Scientists Citing Chu-Song Chen

Zhenan Sun

Zhenan Sun

Chinese Academy of Sciences

Publications: 26

Dacheng Tao

Dacheng Tao

University of Sydney

Publications: 23

Xuelong Li

Xuelong Li

Northwestern Polytechnical University

Publications: 22

Yi-Ping Hung

Yi-Ping Hung

National Taiwan University

Publications: 21

Anil K. Jain

Anil K. Jain

Michigan State University

Publications: 19

Xilin Chen

Xilin Chen

Institute Of Computing Technology

Publications: 19

Shuicheng Yan

Shuicheng Yan

National University of Singapore

Publications: 19

Jinhui Tang

Jinhui Tang

Nanjing University of Science and Technology

Publications: 18

Qi Tian

Qi Tian

Huawei Technologies (China)

Publications: 18

Jiwen Lu

Jiwen Lu

Tsinghua University

Publications: 18

Shiguang Shan

Shiguang Shan

Chinese Academy of Sciences

Publications: 17

Songcan Chen

Songcan Chen

Nanjing University of Aeronautics and Astronautics

Publications: 16

Heng Tao Shen

Heng Tao Shen

University of Electronic Science and Technology of China

Publications: 15

Jie Zhou

Jie Zhou

Tsinghua University

Publications: 15

Joaquim Salvi

Joaquim Salvi

University of Girona

Publications: 15

Ran He

Ran He

Chinese Academy of Sciences

Publications: 14

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