Bin Ji

1.4k citations
31 papers · 856 · 2 hit papers · h-index 9

Impact in

Papers in

Bin Ji

28 papers receiving 841 citations

Bin Ji's Hit Papers

TDN: Temporal Difference Networks for Efficient Action Recognition 2021 · 324 citations
3240+2+4Years since publication100200300

Peers

Bin Ji
Comparison fields: 5 of 94
  • Computer Vision and Pattern Recognition 673
  • Human-Computer Interaction 110
  • Artificial Intelligence 397
  • Biomedical Engineering 259
  • Endocrinology, Diabetes and Metabolism 46
Replace Ingo Fruend with:
Ingo Fruend Canada
Ingo Bax Germany
Yuxin Chen China
Haodong Duan China
Congqi Cao China
Runhao Zeng China
Shugao Ma United States
Abir Das United States
Haocong Rao China
Doyoung Kim South Korea
Bin Ji relative to Ingo Fruend Canada Ingo Fruend's profile →
Citations per field
00.5×1.5×1.8×
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Citations per year

Countries citing papers authored by Bin Ji

Since Specialization
Citations

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

Fields of papers citing papers by Bin Ji

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Bin Ji, 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 Bin Ji Line = papers co-authored together Bin Ji links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 31 papers — load more, or switch the sort, to bring in the rest.

#Work
1
TEA: Temporal Excitation and Aggregation for Action Recognition
Hit paper breakdown →
2020376
2
TDN: Temporal Difference Networks for Efficient Action Recognition
Hit paper breakdown →
2021324
3 202317
4 202015
5 202114
6 202112
7 202211
8 202311
9 20229
10 20218
11 20248
12 20237
13 20167
14 20226
15 20216
16 20234
17 20224
18 20203
19 20222
20 20132

About Bin Ji

Bin Ji is a scholar working on Computer Vision and Pattern Recognition, Biomedical Engineering, Artificial Intelligence, Control and Systems Engineering and Molecular Biology, having authored 31 papers that have together received 856 indexed citations. Recurring topics across this work include Biosensors and Analytical Detection (6 papers), Human Pose and Action Recognition (5 papers), Human Motion and Animation (4 papers), Advanced biosensing and bioanalysis techniques (4 papers), Microfluidic and Capillary Electrophoresis Applications (3 papers), Face recognition and analysis (3 papers), Natural Language Processing Techniques (2 papers) and Multimodal Machine Learning Applications (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (673 citations), Human-Computer Interaction (110 citations), Artificial Intelligence (397 citations), Biomedical Engineering (259 citations) and Endocrinology, Diabetes and Metabolism (46 citations). Bin Ji has collaborated with scholars based in China, United Kingdom and Singapore. Frequent co-authors include Limin Wang, Zhan Tong, Gangshan Wu, Jianguo Zhang, Bin Kang, Xintian Shi, Yan Li, Ye Pan, Shuai Tan and Fang Fang. Their work appears in journals such as Microchemical Journal, IEEE Transactions on Visualization and Computer Graphics, Talanta, Analytical Chemistry and International Journal of Electrical Power & Energy Systems.

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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