Junran Peng

629 citations
22 papers · 324 · h-index 11

Impact in

    • Advanced Neural Network Applications
    • Advanced Image and Video Retrieval Techniques
    • Multimodal Machine Learning Applications
    • Video Surveillance and Tracking Methods
    • Domain Adaptation and Few-Shot Learning
    • Anomaly Detection Techniques and Applications

Papers in

Junran Peng

22 papers receiving 318 citations

Peers

Junran Peng
Comparison fields: 5 of 68
  • Computer Vision and Pattern Recognition 185
  • Artificial Intelligence 142
  • Media Technology 15
  • Health Informatics 2
  • Human-Computer Interaction 8
Replace Jianbiao He with:
Jianbiao He China
Huaidong Zhang China
Seong‐heum Kim South Korea
Gongfan Fang China
Sami Gazzah Tunisia
Kevin J. Shih United States
Shaoxiang Chen China
Xinyi Chen China
Jin Yuan China
Junran Peng relative to Jianbiao He China Jianbiao He's profile →
Citations per field
00.5×1.5×2.5×
Jianbiao He · 1×
Citations per year

Countries citing papers authored by Junran Peng

Since Specialization
Citations

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

Fields of papers citing papers by Junran Peng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 22 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202170
2 202039
3 202132
4 202430
5
Efficient Neural Architecture Transformation Search in Channel-Level for Object Detection
201922
6 202122
7 202418
8 201918
9 201514
10 202313
11 201610
12 20176
13 20225
14 20225
15 20204
16 20244
17 20164
18 20203
19 20222
20 20251

About Junran Peng

Junran Peng is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Control and Systems Engineering, Electrical and Electronic Engineering and Computer Networks and Communications, having authored 22 papers that have together received 324 indexed citations. Recurring topics across this work include Advanced Neural Network Applications (11 papers), Advanced Image and Video Retrieval Techniques (7 papers), Domain Adaptation and Few-Shot Learning (5 papers), Multimodal Machine Learning Applications (3 papers), Human Motion and Animation (2 papers), Orthopedic Infections and Treatments (2 papers), Visual Attention and Saliency Detection (2 papers) and Power Systems Fault Detection (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (185 citations), Artificial Intelligence (142 citations), Media Technology (15 citations), Health Informatics (2 citations) and Human-Computer Interaction (8 citations). Junran Peng has collaborated with scholars based in China, India and United States. Frequent co-authors include Zhaoxiang Zhang, Yuxi Wang, Junjie Yan, Tieniu Tan, Ming Sun, Cong Pan, Jiaheng Liu, Jingyu Liu, Ke Xu and Jie Fu. Their work appears in journals such as IET Generation Transmission & Distribution, IEEE Transactions on Emerging Topics in Computing, Pattern Recognition, International Journal of Computer Vision 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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