Weike Jin

412 citations
14 papers · 259 · h-index 11

Impact in

Papers in

Weike Jin

14 papers receiving 255 citations

Peers

Weike Jin
Comparison fields: 5 of 36
  • Human-Computer Interaction 61
  • Computer Vision and Pattern Recognition 206
  • Developmental and Educational Psychology 49
  • Artificial Intelligence 114
  • Signal Processing 23
Replace Christoph Schmidt with:
Christoph Schmidt Germany
Shruti Palaskar United States
Shengeng Tang China
Deep Kothadiya India
Amit Moryossef Israel
Jakub Kanis Czechia
Sohaïb Laraba Belgium
Dimitar Shterionov Netherlands
Aida Nematzadeh Canada
Tica Lin United States
Weike Jin relative to Christoph Schmidt Germany Christoph Schmidt's profile →
Citations per field
00.5×6.2×
Christoph Schmidt · 1×
Citations per year

Countries citing papers authored by Weike Jin

Since Specialization
Citations

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

Fields of papers citing papers by Weike Jin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

14 of 14 papers shown
#Work
1 201943
2 202233
3 202130
4 202127
5 202122
6 202322
7 202120
8 202112
9 201912
10 202012
11 201910
12 20218
13 20196
14 20192

About Weike Jin

Weike Jin is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Human-Computer Interaction, Developmental and Educational Psychology and Signal Processing, having authored 14 papers that have together received 259 indexed citations. Recurring topics across this work include Multimodal Machine Learning Applications (11 papers), Human Pose and Action Recognition (11 papers), Domain Adaptation and Few-Shot Learning (5 papers), Hand Gesture Recognition Systems (3 papers), Video Analysis and Summarization (3 papers), Topic Modeling (3 papers), Hearing Impairment and Communication (2 papers) and Advanced Image and Video Retrieval Techniques (1 paper). The work is most often cited by research in Human-Computer Interaction (61 citations), Computer Vision and Pattern Recognition (206 citations), Developmental and Educational Psychology (49 citations), Artificial Intelligence (114 citations) and Signal Processing (23 citations). Weike Jin has collaborated with scholars based in China and Sweden. Frequent co-authors include Zhou Zhao, Yueting Zhuang, Jun Xiao, Xiaofei He, Jun Yu, Jieming Zhu, Xiuqiang He, Xingshan Zeng, Fei Wu and Meng Zhang. Their work appears in journals such as IEEE Transactions on Circuits and Systems for Video Technology, IEEE Transactions on Image Processing, IEEE Transactions on Multimedia, ACM Transactions on Multimedia Computing Communications and Applications and 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

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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