Runpeng Cui

1.2k citations
9 papers · 815 · 1 hit paper · h-index 5

Impact in

Papers in

Runpeng Cui

9 papers receiving 773 citations

Runpeng Cui's Hit Papers

A Deep Neural Framework for Continuous Sign Language Recognition by Iterative Training 2019 · 302 citations
3020+2+4Years since publication100200300

Peers

Runpeng Cui
Comparison fields: 5 of 55
  • Human-Computer Interaction 560
  • Developmental and Educational Psychology 364
  • Computer Vision and Pattern Recognition 516
  • Biomedical Engineering 242
  • Artificial Intelligence 129
Replace Lionel Pigou with:
Lionel Pigou Belgium
Hamzah Luqman Saudi Arabia
Razieh Rastgoo Iran
Gaolin Fang China
E. Kiran Kumar India
Ankita Wadhawan India
Philippe Dreuw Germany
G. Anantha Rao India
Walaa Aly Egypt
Runpeng Cui relative to Lionel Pigou Belgium Lionel Pigou's profile →
Citations per field
00.5×1.5×2×2.3×
Lionel Pigou · 1×
Citations per year

Countries citing papers authored by Runpeng Cui

Since Specialization
Citations

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

Fields of papers citing papers by Runpeng Cui

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 13 scholars most cited alongside Runpeng Cui, 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 Runpeng Cui Line = papers co-authored together Runpeng Cui links everyone, so they are left out of the graph.

All Works

9 of 9 papers shown
#Work
1
A Deep Neural Framework for Continuous Sign Language Recognition by Iterative Training
Hit paper breakdown →
2019302
2 2017265
3 2016137
4 201878
5 201923
6 20214
7 20153
8
Rocket Launching: A unified and effecient framework for training well-behaved light net
20172
9 20151

About Runpeng Cui

Runpeng Cui is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Human-Computer Interaction, Control and Systems Engineering and Signal Processing, having authored 9 papers that have together received 815 indexed citations. Recurring topics across this work include Human Pose and Action Recognition (4 papers), Hand Gesture Recognition Systems (3 papers), Advanced Image and Video Retrieval Techniques (3 papers), Multimodal Machine Learning Applications (3 papers), Machine Learning and Data Classification (2 papers), Advanced Neural Network Applications (2 papers), Stock Market Forecasting Methods (1 paper) and Human Motion and Animation (1 paper). The work is most often cited by research in Human-Computer Interaction (560 citations), Developmental and Educational Psychology (364 citations), Computer Vision and Pattern Recognition (516 citations), Biomedical Engineering (242 citations) and Artificial Intelligence (129 citations). Runpeng Cui has collaborated with scholars based in China and United States. Frequent co-authors include Changshui Zhang, Hu Liu, Hu Liu, Kun Fu, Fei Sha, Junqi Jin, Xiaoqiang Zhu, Guorui Zhou, Ying Fan and Weijie Bian. Their work appears in journals such as IEEE Transactions on Multimedia, Neurocomputing, IEEE Transactions on Pattern Analysis and Machine Intelligence, Proceedings of the AAAI Conference on Artificial Intelligence and arXiv (Cornell University).

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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