Beibei Lin

599 citations
16 papers · 325 · 1 hit paper · h-index 8

Impact in

Papers in

Beibei Lin

16 papers receiving 321 citations

Beibei Lin's Hit Papers

Gait Recognition via Effective Global-Local Feature Representation and Local Temporal Aggregation 2021 · 194 citations
1940+1+3Years since publication50100150

Peers

Beibei Lin
Comparison fields: 5 of 66
  • Human-Computer Interaction 100
  • Computer Vision and Pattern Recognition 234
  • Biomedical Engineering 229
  • Endocrinology, Diabetes and Metabolism 60
  • Media Technology 17
Replace Miwa Okumura with:
Miwa Okumura Japan
Yunjie Peng China
Chuanfu Shen China
Haruyuki Iwama Japan
Toby H. W. Lam Hong Kong
Vinay Bettadapura United States
Daoliang Tan China
Lucia Migliorelli Italy
Philipp Stefan Germany
Aneeq Zia United States
Beibei Lin relative to Miwa Okumura Japan Miwa Okumura's profile →
Citations per field
00.5×6.4×
Miwa Okumura · 1×
Citations per year

Countries citing papers authored by Beibei Lin

Since Specialization
Citations

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

Fields of papers citing papers by Beibei Lin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

16 of 16 papers shown
#Work
1
Gait Recognition via Effective Global-Local Feature Representation and Local Temporal Aggregation
Hit paper breakdown →
2021194
2 202336
3 202326
4 201413
5 202111
6 20239
7 20229
8 20197
9 20224
10 20224
11 20213
12 20213
13 20252
14 20222
15 20251
16 20211

About Beibei Lin

Beibei Lin is a scholar working on Computer Vision and Pattern Recognition, Biomedical Engineering, Human-Computer Interaction, Rehabilitation and Obstetrics and Gynecology, having authored 16 papers that have together received 325 indexed citations. Recurring topics across this work include Gait Recognition and Analysis (5 papers), Video Surveillance and Tracking Methods (4 papers), Hand Gesture Recognition Systems (4 papers), Human Pose and Action Recognition (4 papers), Stroke Rehabilitation and Recovery (2 papers), Glaucoma and retinal disorders (1 paper), Image Processing Techniques and Applications (1 paper) and Pain Management and Opioid Use (1 paper). The work is most often cited by research in Human-Computer Interaction (100 citations), Computer Vision and Pattern Recognition (234 citations), Biomedical Engineering (229 citations), Endocrinology, Diabetes and Metabolism (60 citations) and Media Technology (17 citations). Beibei Lin has collaborated with scholars based in China, Singapore and Australia. Frequent co-authors include Shunli Zhang, Xin Yu, Robby T. Tan, Yeying Jin, Wending Yan, Yehuan Liu, Yang Tian, Zheng Zhu, Ming Wang and Lincheng Li. Their work appears in journals such as IEEE Signal Processing Letters, Annals of Palliative Medicine, Medicine, BMC Psychiatry and BMC Neurology.

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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