Bin Ji

1.3k citations
30 papers · 822 · 2 hit papers · h-index 9

Impact in

Papers in

Bin Ji

26 papers receiving 804 citations

Bin Ji's Hit Papers

TDN: Temporal Difference Networks for Efficient Action Recognition 2021 · 310 citations
3100+2+4Years since publication100200300

Peers

Bin Ji
Comparison fields: 5 of 91
  • Computer Vision and Pattern Recognition 650
  • Human-Computer Interaction 105
  • Artificial Intelligence 389
  • Biomedical Engineering 247
  • Endocrinology, Diabetes and Metabolism 46
Replace Ingo Fruend with:
Ingo Fruend Canada
Ingo Bax Germany
Congqi Cao China
Yuxin Chen China
Abir Das United States
Shugao Ma United States
Marco Cannici Switzerland
Minlong Lu China
Nazlı İkizler-Cinbiş Türkiye
Djamila Romaissa Beddiar Finland
Bin Ji relative to Ingo Fruend Canada Ingo Fruend's profile →
Citations per field
00.5×1.5×1.8×
Ingo Fruend · 1×
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 30 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 →
2020368
2
TDN: Temporal Difference Networks for Efficient Action Recognition
Hit paper breakdown →
2021310
3 202315
4 202014
5 202113
6 202112
7 202210
8 20229
9 20239
10 20218
11 20237
12 20167
13 20246
14 20226
15 20216
16 20224
17 20203
18 20233
19 20192
20 20132

About Bin Ji

Bin Ji is a scholar working on Computer Vision and Pattern Recognition, Biomedical Engineering, Artificial Intelligence, Molecular Biology and Control and Systems Engineering, having authored 30 papers that have together received 822 indexed citations. Recurring topics across this work include Biosensors and Analytical Detection (6 papers), Advanced biosensing and bioanalysis techniques (5 papers), Human Pose and Action Recognition (5 papers), Human Motion and Animation (4 papers), SARS-CoV-2 detection and testing (3 papers), Microfluidic and Capillary Electrophoresis Applications (3 papers), Face recognition and analysis (3 papers) and Natural Language Processing Techniques (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (650 citations), Human-Computer Interaction (105 citations), Artificial Intelligence (389 citations), Biomedical Engineering (247 citations) and Endocrinology, Diabetes and Metabolism (46 citations). Bin Ji has collaborated with scholars based in China, United Kingdom and Belarus. Frequent co-authors include Limin Wang, Zhan Tong, Gangshan Wu, Bin Kang, Xintian Shi, Yan Li, Jianguo Zhang, Ye Pan, Fang Fang and Zhiyong Wu. Their work appears in journals such as Talanta, Microchemical Journal, IEEE Transactions on Cybernetics, Small Methods and Analytical Chemistry.

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.

Explore authors with similar magnitude of impact