D-Index & Metrics Best Publications

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 70 Citations 19,169 339 World Ranking 839 National Ranking 72

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Machine learning
  • Algorithm

Heng Tao Shen focuses on Artificial intelligence, Hash function, Theoretical computer science, Data mining and Pattern recognition. The various areas that he examines in his Artificial intelligence study include Machine learning and Graph. His biological study spans a wide range of topics, including Binary code, Search engine indexing and Image retrieval.

His Data mining research integrates issues from Object, Motion, Algorithm design and Motion estimation. His study in the field of Discriminative model is also linked to topics like Kernel principal component analysis. His studies deal with areas such as Universal hashing and Dynamic perfect hashing as well as Feature hashing.

His most cited work include:

  • Supervised Discrete Hashing (630 citations)
  • A Survey on Learning to Hash (485 citations)
  • l 2,1 -norm regularized discriminative feature selection for unsupervised learning (468 citations)

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

His primary scientific interests are in Artificial intelligence, Pattern recognition, Data mining, Machine learning and Hash function. His Artificial intelligence study frequently involves adjacent topics like Computer vision. His work deals with themes such as Contextual image classification, Embedding and Cluster analysis, which intersect with Pattern recognition.

As part of one scientific family, he deals mainly with the area of Data mining, narrowing it down to issues related to the Search engine indexing, and often Video tracking. In the field of Machine learning, his study on Feature overlaps with subjects such as Modal. Heng Tao Shen has included themes like Binary code and Theoretical computer science in his Hash function study.

He most often published in these fields:

  • Artificial intelligence (49.88%)
  • Pattern recognition (25.41%)
  • Data mining (17.65%)

What were the highlights of his more recent work (between 2018-2021)?

  • Artificial intelligence (49.88%)
  • Pattern recognition (25.41%)
  • Machine learning (15.76%)

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

Heng Tao Shen mainly investigates Artificial intelligence, Pattern recognition, Machine learning, Discriminative model and Embedding. Heng Tao Shen performs integrative Artificial intelligence and Focus research in his work. His Pattern recognition research includes elements of Contextual image classification and Benchmark.

His work on Feature as part of general Machine learning research is frequently linked to Modal, Knowledge transfer and Scheme, thereby connecting diverse disciplines of science. His Discriminative model research incorporates elements of Iterative method, Hash function and Binary code. His work carried out in the field of Feature extraction brings together such families of science as Semantics and Natural language.

Between 2018 and 2021, his most popular works were:

  • Transfer Independently Together: A Generalized Framework for Domain Adaptation (133 citations)
  • From Deterministic to Generative: Multimodal Stochastic RNNs for Video Captioning (125 citations)
  • Binary Multi-View Clustering (121 citations)

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

  • Artificial intelligence
  • Machine learning
  • Algorithm

The scientist’s investigation covers issues in Artificial intelligence, Pattern recognition, Theoretical computer science, Binary code and Feature extraction. His Artificial intelligence research is multidisciplinary, incorporating perspectives in Machine learning and Natural language processing. Heng Tao Shen combines subjects such as Contextual image classification, Similarity, Facial expression recognition and Feature with his study of Pattern recognition.

His studies in Theoretical computer science integrate themes in fields like Hash function, Divergence and Graph. The Hash function study combines topics in areas such as Hamming space, Multimedia search and Image retrieval. Heng Tao Shen interconnects Text mining and Semantics in the investigation of issues within Feature extraction.

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

Supervised Discrete Hashing

Fumin Shen;Chunhua Shen;Wei Liu;Heng Tao Shen.
computer vision and pattern recognition (2015)

663 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

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

Hashing for Similarity Search: A Survey

Jingdong Wang;Heng Tao Shen;Jingkuan Song;Jianqiu Ji.
arXiv: Data Structures and Algorithms (2014)

555 Citations

Discovery of convoys in trajectory databases

Hoyoung Jeung;Man Lung Yiu;Xiaofang Zhou;Christian S. Jensen.
very large data bases (2008)

480 Citations

A Survey on Learning to Hash

Jingdong Wang;Ting Zhang;Jingkuan Song;Nicu Sebe.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2018)

426 Citations

Inter-media hashing for large-scale retrieval from heterogeneous data sources

Jingkuan Song;Yang Yang;Yi Yang;Zi Huang.
international conference on management of data (2013)

392 Citations

Discovering popular routes from trajectories

Zaiben Chen;Heng Tao Shen;Xiaofang Zhou.
international conference on data engineering (2011)

383 Citations

A Hybrid Prediction Model for Moving Objects

Hoyoung Jeung;Qing Liu;Heng Tao Shen;Xiaofang Zhou.
international conference on data engineering (2008)

363 Citations

Adversarial Cross-Modal Retrieval

Bokun Wang;Yang Yang;Xing Xu;Alan Hanjalic.
acm multimedia (2017)

355 Citations

Best Scientists Citing Heng Tao Shen

Xiaofang Zhou

Xiaofang Zhou

Hong Kong University of Science and Technology

Publications: 70

Yang Yang

Yang Yang

University of Electronic Science and Technology of China

Publications: 65

Dacheng Tao

Dacheng Tao

University of Sydney

Publications: 63

Xuelong Li

Xuelong Li

Northwestern Polytechnical University

Publications: 63

Zi Huang

Zi Huang

University of Queensland

Publications: 62

Fumin Shen

Fumin Shen

University of Electronic Science and Technology of China

Publications: 62

Yi Yang

Yi Yang

Zhejiang University

Publications: 57

Feiping Nie

Feiping Nie

Northwestern Polytechnical University

Publications: 49

Ling Shao

Ling Shao

Inception Institute of Artificial Intelligence

Publications: 48

Qi Tian

Qi Tian

Huawei Technologies (China)

Publications: 46

Kai Zheng

Kai Zheng

Huawei Technologies (China)

Publications: 46

Meng Wang

Meng Wang

Hefei University of Technology

Publications: 43

Lei Chen

Lei Chen

Hong Kong University of Science and Technology

Publications: 40

Jingkuan Song

Jingkuan Song

Columbia University

Publications: 39

Yu Zheng

Yu Zheng

Jingdong (China)

Publications: 35

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

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