Hai Jin

416 citations
9 papers · 88 indexed · h-index 6
Topics
Face recognition and analysis (3 papers)Topic Modeling (2 papers)Image Retrieval and Classification Techniques (2 papers)
Journals
SHILAP Revista de lepidopterologíaInformation FusionComputer Aided Geometric Design

In The Last Decade

Hai Jin

7 papers receiving 84 citations

Peers

Hai Jin
Comparison fields: 5 of 37
  • Computer Vision and Pattern Recognition 47
  • Computer Networks and Communications 28
  • Artificial Intelligence 17
  • Computational Mechanics 14
  • Information Systems 12
Replace Michael J. Klaiber with:
Michael J. Klaiber Germany
Jinnian Zhang China
Hugo Latapie United States
Y. Ono Japan
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Pouya Samangouei United States
J. Howard Frank Germany
Guangxuan Xiao United States
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Hai Jin relative to Michael J. Klaiber Germany Michael J. Klaiber's profile →
Citations per field
00.5×4.7×
Michael J. Klaiber · 1×
Citations per year

Countries citing papers authored by Hai Jin

Since Specialization
Citations

This map shows the geographic impact of Hai Jin's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Hai Jin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hai Jin more than expected).

Fields of papers citing papers by Hai Jin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hai Jin. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Hai Jin. The network helps show where Hai Jin may publish in the future.

Co-authorship network of co-authors of Hai Jin

This figure shows the co-authorship network connecting the top 25 collaborators of Hai Jin. A scholar is included among the top collaborators of Hai Jin based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Hai Jin. Hai Jin is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

9 of 9 papers shown
#WorkIndexed citations
1 2
2 0
3 0
4 10
5 7
6 23
7 17
8 21
9
Article 1 A. M. Bronstein Shape Google: Geometric Words and Expressions for (20 pages) M. M. Bronstein Invariant Shape Retrieval
8

About Hai Jin

Hai Jin is a scholar working on Computer Vision and Pattern Recognition, Management Science and Operations Research and Signal Processing, having authored 9 papers that have together received 88 indexed citations. Recurring topics across this work include Face recognition and analysis (3 papers), Topic Modeling (2 papers) and Image Retrieval and Classification Techniques (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (47 citations), Computer Networks and Communications (28 citations) and Human-Computer Interaction (4 citations). Hai Jin has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Jing Hua, Xiaokang Wang, Xun Wang, Zichun Zhong, Xun Wang, Chuan Li, Mark Berman, Yuehua Wang, Hongwei Zhang and Abhimanyu Gosain. Their work appears in journals such as SHILAP Revista de lepidopterología, Information Fusion and Computer Aided Geometric Design.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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