Kan Jin

585 citations
9 papers · 443 · 1 hit paper · h-index 7

Impact in

Papers in

Kan Jin

9 papers receiving 436 citations

Kan Jin's Hit Papers

Attention mechanism-based CNN for facial expression recognition 2020 · 239 citations
2390+2+4Years since publication50100150200

Peers

Kan Jin
Comparison fields: 5 of 69
  • Computer Vision and Pattern Recognition 226
  • Experimental and Cognitive Psychology 122
  • Aerospace Engineering 154
  • Media Technology 46
  • Urban Studies 22
Replace Zilu Ying with:
Zilu Ying China
Mohsen Ardabilian France
Thomas S. Huang United States
Joseph Ronsin France
Qi Jia China
Di Lu China
Fengliang Xu United States
Hassan Farsi Iran
M. Sami Zitouni United Arab Emirates
Kan Jin relative to Zilu Ying China Zilu Ying's profile →
Citations per field
00.5×3.3×
Zilu Ying · 1×
Citations per year

Countries citing papers authored by Kan Jin

Since Specialization
Citations

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

Fields of papers citing papers by Kan Jin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 23 scholars most cited alongside Kan Jin, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Kan Jin Line = papers co-authored together Kan Jin links everyone, so they are left out of the graph.

All Works

9 of 9 papers shown
#Work
1
Attention mechanism-based CNN for facial expression recognition
Hit paper breakdown →
2020239
2 202068
3 201956
4 201636
5 201915
6 202314
7 20159
8 20155
9 20191

About Kan Jin

Kan Jin is a scholar working on Aerospace Engineering, Computer Vision and Pattern Recognition, Media Technology, Ocean Engineering and Biomedical Engineering, having authored 9 papers that have together received 443 indexed citations. Recurring topics across this work include Advanced SAR Imaging Techniques (4 papers), Synthetic Aperture Radar (SAR) Applications and Techniques (4 papers), Remote-Sensing Image Classification (2 papers), Geophysical Methods and Applications (2 papers), Optical Systems and Laser Technology (1 paper), Optical measurement and interference techniques (1 paper), Microwave Imaging and Scattering Analysis (1 paper) and Image and Signal Denoising Methods (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (226 citations), Experimental and Cognitive Psychology (122 citations), Aerospace Engineering (154 citations), Media Technology (46 citations) and Urban Studies (22 citations). Kan Jin has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Jing Li, Dalin Zhou, Zhaojie Ju, Naoyuki Kubota, Jian Yang, Jian Yang, Junjun Yin, Hang Chen, Liang Zeng and Bin Xu. Their work appears in journals such as IEEE Transactions on Geoscience and Remote Sensing, Sensors, IET Radar Sonar & Navigation, IEEE Geoscience and Remote Sensing Letters and Neurocomputing.

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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