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 57 Citations 12,557 348 World Ranking 1921 National Ranking 175

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Machine learning
  • Computer vision

Yongdong Zhang focuses on Artificial intelligence, Computer vision, Pattern recognition, Data mining and Feature extraction. His research combines Machine learning and Artificial intelligence. His Computer vision study combines topics in areas such as Artificial neural network and Time complexity.

The study incorporates disciplines such as Receptive field, Parsing, Convolution, Differentiable function and Kernel in addition to Pattern recognition. In general Data mining, his work in Identification is often linked to mHealth linking many areas of study. As part of the same scientific family, Yongdong Zhang usually focuses on Feature extraction, concentrating on Feature and intersecting with Joint and Representation.

His most cited work include:

  • Deep Learning for Content-Based Image Retrieval: A Comprehensive Study (565 citations)
  • Multiview Spectral Embedding (385 citations)
  • Efficient Parallel Framework for HEVC Motion Estimation on Many-Core Processors (344 citations)

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

Yongdong Zhang mostly deals with Artificial intelligence, Pattern recognition, Computer vision, Machine learning and Feature extraction. Feature, Image retrieval, Image, Convolutional neural network and Segmentation are the primary areas of interest in his Artificial intelligence study. Yongdong Zhang has included themes like Cluster analysis and Robustness in his Pattern recognition study.

His research on Computer vision often connects related areas such as Frame. Machine learning is frequently linked to Data mining in his study. Information retrieval is closely connected to Visualization in his research, which is encompassed under the umbrella topic of Feature extraction.

He most often published in these fields:

  • Artificial intelligence (56.70%)
  • Pattern recognition (23.21%)
  • Computer vision (22.97%)

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

  • Artificial intelligence (56.70%)
  • Pattern recognition (23.21%)
  • Machine learning (12.68%)

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

His primary areas of study are Artificial intelligence, Pattern recognition, Machine learning, Image and Discriminative model. His Computer vision research extends to Artificial intelligence, which is thematically connected. His work carried out in the field of Pattern recognition brings together such families of science as Pixel, Deep learning, Pooling and Similarity.

Yongdong Zhang has researched Machine learning in several fields, including Semantics and Reliability. The Image study combines topics in areas such as Translation, Relation, Information retrieval, Algorithm and Key. His study focuses on the intersection of Discriminative model and fields such as Feature learning with connections in the field of Training set and Feature.

Between 2018 and 2021, his most popular works were:

  • Deep Representation Learning With Part Loss for Person Re-Identification (153 citations)
  • Automated pulmonary nodule detection in CT images using deep convolutional neural networks (134 citations)
  • Cross-Modality Bridging and Knowledge Transferring for Image Understanding (124 citations)

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

  • Artificial intelligence
  • Machine learning
  • Computer vision

His scientific interests lie mostly in Artificial intelligence, Closed captioning, Pattern recognition, Artificial neural network and Convolutional neural network. His Artificial intelligence research includes elements of Machine learning, Computer vision and Natural language processing. His Computer vision research is multidisciplinary, relying on both Deep learning and Boundary.

His studies in Closed captioning integrate themes in fields like Speech recognition and Natural language. The Pattern recognition study combines topics in areas such as Consistency and Scale. His work deals with themes such as Character, Computer-aided diagnosis, Discriminative model and Sequence, which intersect with Convolutional neural network.

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 for Content-Based Image Retrieval: A Comprehensive Study

Ji Wan;Dayong Wang;Steven Chu Hong Hoi;Pengcheng Wu.
acm multimedia (2014)

824 Citations

A density-based method for adaptive LDA model selection

Juan Cao;Tian Xia;Jintao Li;Yongdong Zhang.
Neurocomputing (2009)

424 Citations

Multiview Spectral Embedding

Tian Xia;Dacheng Tao;Tao Mei;Yongdong Zhang.
systems man and cybernetics (2010)

407 Citations

Efficient Parallel Framework for HEVC Motion Estimation on Many-Core Processors

Chenggang Clarence Yan;Yongdong Zhang;Jizheng Xu;Feng Dai.
IEEE Transactions on Circuits and Systems for Video Technology (2014)

392 Citations

A Highly Parallel Framework for HEVC Coding Unit Partitioning Tree Decision on Many-core Processors

Chenggang Yan;Yongdong Zhang;Jizheng Xu;Feng Dai.
IEEE Signal Processing Letters (2014)

350 Citations

Drug–target interaction prediction: databases, web servers and computational models

Xing Chen;Chenggang Clarence Yan;Xiaotian Zhang;Xu Zhang.
Briefings in Bioinformatics (2016)

325 Citations

WBSMDA: Within and Between Score for MiRNA-Disease Association prediction.

Xing Chen;Chenggang Clarence Yan;Chenggang Clarence Yan;Xu Zhang;Zhu-Hong You.
Scientific Reports (2016)

240 Citations

Deep Representation Learning With Part Loss for Person Re-Identification

Hantao Yao;Shiliang Zhang;Richang Hong;Yongdong Zhang.
IEEE Transactions on Image Processing (2019)

231 Citations

Supervised Hash Coding With Deep Neural Network for Environment Perception of Intelligent Vehicles

Chenggang Yan;Hongtao Xie;Dongbao Yang;Jian Yin.
IEEE Transactions on Intelligent Transportation Systems (2018)

224 Citations

Multi-task deep visual-semantic embedding for video thumbnail selection

Wu Liu;Tao Mei;Yongdong Zhang;Cherry Che.
computer vision and pattern recognition (2015)

183 Citations

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Best Scientists Citing Yongdong Zhang

Dacheng Tao

Dacheng Tao

University of Sydney

Publications: 68

Xing Chen

Xing Chen

China University of Mining and Technology

Publications: 63

Qi Tian

Qi Tian

Huawei Technologies (China)

Publications: 61

Zheng-Jun Zha

Zheng-Jun Zha

University of Science and Technology of China

Publications: 46

Yehoshua Y. Zeevi

Yehoshua Y. Zeevi

Technion – Israel Institute of Technology

Publications: 43

Qingming Huang

Qingming Huang

Chinese Academy of Sciences

Publications: 41

Tat-Seng Chua

Tat-Seng Chua

National University of Singapore

Publications: 40

Zhu-Hong You

Zhu-Hong You

Chinese Academy of Sciences

Publications: 40

Xuelong Li

Xuelong Li

Northwestern Polytechnical University

Publications: 40

Xiangnan He

Xiangnan He

University of Science and Technology of China

Publications: 37

Meng Wang

Meng Wang

Hefei University of Technology

Publications: 34

Huadong Ma

Huadong Ma

Beijing University of Posts and Telecommunications

Publications: 29

Ling Shao

Ling Shao

Inception Institute of Artificial Intelligence

Publications: 29

Andreas Uhl

Andreas Uhl

University of Salzburg

Publications: 27

Liqiang Nie

Liqiang Nie

Shandong University

Publications: 23

Tao Mei

Tao Mei

Jingdong (China)

Publications: 23

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