H-Index & Metrics Best Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science D-index 121 Citations 56,262 601 World Ranking 44 National Ranking 28

Research.com Recognitions

Awards & Achievements

2017 - ACM Fellow For contributions to large-scale multimedia content recognition and multimedia information retrieval

2010 - Fellow of the American Association for the Advancement of Science (AAAS)

2009 - IEEE Kiyo Tomiyasu Award “For contributions to Automated Image Classification.”

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Machine learning
  • Statistics

His main research concerns Artificial intelligence, Computer vision, Pattern recognition, Machine learning and Information retrieval. His study in Feature extraction, Image processing, Image, Support vector machine and Search engine indexing are all subfields of Artificial intelligence. The concepts of his Pattern recognition study are interwoven with issues in Feature detection, Hash function, Feature and Image retrieval.

Shih-Fu Chang focuses mostly in the field of Image retrieval, narrowing it down to matters related to Data mining and, in some cases, Similarity. His research investigates the connection with Machine learning and areas like Syntax which intersect with concerns in Hidden Markov model. His Information retrieval research incorporates elements of Annotation, World Wide Web, Benchmark and TRECVID.

His most cited work include:

  • VisualSEEk: a fully automated content-based image query system (1744 citations)
  • Supervised hashing with kernels (1111 citations)
  • Hashing with Graphs (848 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, Computer vision, Multimedia and Information retrieval. His Artificial intelligence research is multidisciplinary, incorporating perspectives in Machine learning and Natural language processing. Shih-Fu Chang has included themes like Training set and Data mining in his Machine learning study.

The various areas that he examines in his Pattern recognition study include Contextual image classification, Object detection and Feature. Shih-Fu Chang interconnects World Wide Web and Automatic summarization in the investigation of issues within Multimedia. His Information retrieval study frequently links to related topics such as TRECVID.

He most often published in these fields:

  • Artificial intelligence (58.93%)
  • Pattern recognition (22.64%)
  • Computer vision (22.64%)

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

  • Artificial intelligence (58.93%)
  • Pattern recognition (22.64%)
  • Natural language processing (6.68%)

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

Shih-Fu Chang focuses on Artificial intelligence, Pattern recognition, Natural language processing, Machine learning and Embedding. His research on Artificial intelligence often connects related areas such as Computer vision. His Pattern recognition study combines topics in areas such as Hash function, Feature and Image retrieval.

His studies in Natural language processing integrate themes in fields like Ontology, Context, Language acquisition and Referring expression. His Machine learning research is multidisciplinary, relying on both Training set and Categorization. His Embedding study also includes

  • Multimedia and Semantics most often made with reference to Space,
  • Invariant most often made with reference to Softmax function.

Between 2015 and 2021, his most popular works were:

  • Temporal Action Localization in Untrimmed Videos via Multi-stage CNNs (404 citations)
  • CDC: Convolutional-De-Convolutional Networks for Precise Temporal Action Localization in Untrimmed Videos (307 citations)
  • Learning to Hash for Indexing Big Data—A Survey (295 citations)

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

  • Artificial intelligence
  • Machine learning
  • Statistics

His primary areas of study are Artificial intelligence, Pattern recognition, Computer vision, Machine learning and Embedding. His Artificial intelligence study typically links adjacent topics like Natural language processing. His Pattern recognition research includes elements of Frame, Pixel, Image and Feature.

His work in the fields of Computer vision, such as Image segmentation and Segmentation, intersects with other areas such as Function, Initialization and Multi stage. His Regularization study in the realm of Machine learning connects with subjects such as Class. His work in Embedding addresses issues such as Softmax function, which are connected to fields such as Invariant, Supervised learning and Feature vector.

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

VisualSEEk: a fully automated content-based image query system

John R. Smith;Shih-Fu Chang.
acm multimedia (1997)

2954 Citations

Supervised hashing with kernels

Wei Liu;Jun Wang;Rongrong Ji;Yu-Gang Jiang.
computer vision and pattern recognition (2012)

1236 Citations

Hashing with Graphs

Wei Liu;Jun Wang;Sanjiv Kumar;Shih-fu Chang.
international conference on machine learning (2011)

931 Citations

Tools and techniques for color image retrieval

John R. Smith;Shih-Fu Chang.
Storage and Retrieval for Image and Video Databases (1996)

905 Citations

A robust image authentication method distinguishing JPEG compression from malicious manipulation

Ching-Yung Lin;Shih-Fu Chang.
IEEE Transactions on Circuits and Systems for Video Technology (2001)

763 Citations

Semi-Supervised Hashing for Large-Scale Search

Jun Wang;S. Kumar;Shih-Fu Chang.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2012)

740 Citations

Large-scale concept ontology for multimedia

M. Naphade;J.R. Smith;J. Tesic;Shih-Fu Chang.
IEEE MultiMedia (2006)

735 Citations

A robust content based digital signature for image authentication

M. Schneider;Shih-Fu Chang.
international conference on image processing (1996)

705 Citations

Overview of the MPEG-7 standard

Shih-Fu Chang;T. Sikora;A. Purl.
IEEE Transactions on Circuits and Systems for Video Technology (2001)

655 Citations

Semi-supervised hashing for scalable image retrieval

Jun Wang;Sanjiv Kumar;Shih-Fu Chang.
computer vision and pattern recognition (2010)

644 Citations

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Best Scientists Citing Shih-Fu Chang

Qi Tian

Qi Tian

Huawei Technologies (China)

Publications: 204

Tat-Seng Chua

Tat-Seng Chua

National University of Singapore

Publications: 131

Tao Mei

Tao Mei

Jingdong (China)

Publications: 120

Thomas S. Huang

Thomas S. Huang

University of Illinois at Urbana-Champaign

Publications: 111

Meng Wang

Meng Wang

Hefei University of Technology

Publications: 106

Jiebo Luo

Jiebo Luo

University of Rochester

Publications: 102

Dacheng Tao

Dacheng Tao

University of Sydney

Publications: 99

Xian-Sheng Hua

Xian-Sheng Hua

Microsoft (United States)

Publications: 94

Alexander G. Hauptmann

Alexander G. Hauptmann

Carnegie Mellon University

Publications: 94

Heng Tao Shen

Heng Tao Shen

University of Electronic Science and Technology of China

Publications: 92

Cees G. M. Snoek

Cees G. M. Snoek

University of Amsterdam

Publications: 88

Chong-Wah Ngo

Chong-Wah Ngo

Singapore Management University

Publications: 87

Changsheng Xu

Changsheng Xu

Chinese Academy of Sciences

Publications: 86

Wei Liu

Wei Liu

Tencent (China)

Publications: 84

Jianping Fan

Jianping Fan

University of North Carolina at Charlotte

Publications: 83

Marcel Worring

Marcel Worring

University of Amsterdam

Publications: 76

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