Jesse S. Jin

207 total papers · 3.3k total citations
126 papers, 2.2k citations indexed

About

Jesse S. Jin is a scholar working on Computer Vision and Pattern Recognition, Signal Processing and Artificial Intelligence. According to data from OpenAlex, Jesse S. Jin has authored 126 papers receiving a total of 2.2k indexed citations (citations by other indexed papers that have themselves been cited), including 103 papers in Computer Vision and Pattern Recognition, 22 papers in Signal Processing and 17 papers in Artificial Intelligence. Recurrent topics in Jesse S. Jin's work include Video Analysis and Summarization (33 papers), Image Retrieval and Classification Techniques (30 papers) and Advanced Image and Video Retrieval Techniques (29 papers). Jesse S. Jin is often cited by papers focused on Video Analysis and Summarization (33 papers), Image Retrieval and Classification Techniques (30 papers) and Advanced Image and Video Retrieval Techniques (29 papers). Jesse S. Jin collaborates with scholars based in Australia, China and Singapore. Jesse S. Jin's co-authors include Suhuai Luo, Xian-Feng Han, Wei Jiang, Richard Yi Da Xu, Min Xu, John G. Allen, Liping Xiao, Mingjie Wang, Lei Gao and Ling‐Yu Duan and has published in prestigious journals such as PLoS ONE, NeuroImage and Sensors.

In The Last Decade

Jesse S. Jin

120 papers receiving 2.1k citations

Hit Papers

A review of algorithms fo... 2017 2026 2020 2023 2017 50 100 150 200 250

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Jesse S. Jin 1.2k 278 275 245 243 126 2.2k
Yong‐Sheng Chen 560 0.5× 417 1.5× 133 0.5× 132 0.5× 98 0.4× 158 2.0k
Jan Cornelis 1.6k 1.3× 211 0.8× 603 2.2× 68 0.3× 336 1.4× 288 3.2k
N. Alberto Borghese 711 0.6× 770 2.8× 49 0.2× 304 1.2× 260 1.1× 154 3.1k
Shihui Ying 998 0.8× 172 0.6× 57 0.2× 103 0.4× 651 2.7× 122 2.2k
Marco Leo 1.5k 1.2× 319 1.1× 180 0.7× 39 0.2× 315 1.3× 134 3.0k
Luis Enrique Sucar 1.1k 0.9× 169 0.6× 168 0.6× 60 0.2× 1.0k 4.2× 215 2.9k
Umberto Castellani 937 0.8× 207 0.7× 56 0.2× 58 0.2× 218 0.9× 90 1.5k
Yi‐Ping Hung 1.7k 1.4× 571 2.1× 220 0.8× 29 0.1× 190 0.8× 193 2.8k
David Marshall 870 0.7× 268 1.0× 141 0.5× 15 0.1× 254 1.0× 96 2.4k
Hubert P. H. Shum 1.1k 0.9× 244 0.9× 163 0.6× 64 0.3× 339 1.4× 151 2.3k

Countries citing papers authored by Jesse S. Jin

Since Specialization
Citations

This map shows the geographic impact of Jesse S. 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 Jesse S. Jin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jesse S. Jin more than expected).

Fields of papers citing papers by Jesse S. Jin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jesse S. 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 Jesse S. Jin. The network helps show where Jesse S. Jin may publish in the future.

Co-authorship network of co-authors of Jesse S. Jin

This figure shows the co-authorship network connecting the top 25 collaborators of Jesse S. Jin. A scholar is included among the top collaborators of Jesse S. 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 Jesse S. Jin. Jesse S. Jin is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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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