Wei Peng
Impact in
- Computational Mathematics top 1%
-
- Human Pose and Action Recognition
- Face and Expression Recognition
- Image Retrieval and Classification Techniques
- Data Visualization and Analytics
Papers in
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- Tensor decomposition and applications 7
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- Human Pose and Action Recognition 14
- Image Retrieval and Classification Techniques 9
- Face and Expression Recognition 7
- Co-authors
- Tao LiChris DingGuoying ZhaoHaesun ParkXiaopeng HongElke A. RundensteinerMatthew O. WardHaoyu Chen
- Journals
- Scientific Reports (2 papers)IEEE Transactions on Multimedia (2 papers)IEEE Transactions on Affective Computing (2 papers)Pattern Recognition (2 papers)Resources Conservation and Recycling (1 paper)
- Partner nations
- United StatesChinaFinland
In The Last Decade
Wei Peng
108 papers receiving 3.1k citations
Hit Papers
Peers
Comparison fields: 5 of 154
- Computational Mathematics 81
- Computer Vision and Pattern Recognition 1.5k
- Health Informatics 60
- Artificial Intelligence 1.4k
- Signal Processing 335
Countries citing papers authored by Wei Peng
This map shows the geographic impact of Wei 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 Wei Peng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Wei Peng more than expected).
Fields of papers citing papers by Wei Peng
This network shows the impact of papers produced by Wei 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 Wei Peng. The network helps show where Wei Peng may publish in the future.
Co-authors
The 25 scholars most cited alongside Wei Peng, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2024 | 5 | |
| 2 | 2024 | 1 | |
| 3 | 2024 | 4 | |
| 4 | 2024 | 0 | |
| 5 | 2024 | 2 | |
| 6 | 2024 | 5 | |
| 7 | 2024 | 11 | |
| 8 | Large Language Models in Healthcare and Medical Domain: A Review Hit paper breakdown → | 2024 | 127 |
| 9 | 2023 | 1 | |
| 10 | 2023 | 10 | |
| 11 | 2023 | 9 | |
| 12 | 2023 | 21 | |
| 13 | 2023 | 4 | |
| 14 | 2023 | 2 | |
| 15 | 2023 | 1 | |
| 16 | 2022 | 14 | |
| 17 | 2021 | 52 | |
| 18 | 2021 | 37 | |
| 19 | A Study of Hydrodynamic Characteristics of an Underwater On-line Condenser-cleaning Robot | 2008 | 0 |
| 20 | Orthogonal nonnegative matrix t-factorizations for clustering Hit paper breakdown → | 2006 | 848 |
About Wei Peng
Wei Peng is a scholar working on Computational Mathematics, Computer Vision and Pattern Recognition, Signal Processing, Artificial Intelligence and Information Systems, having authored 123 papers that have together received 3.3k indexed citations. Recurring topics across this work include Human Pose and Action Recognition (14 papers), Data Mining Algorithms and Applications (9 papers), Image Retrieval and Classification Techniques (9 papers), Topic Modeling (8 papers), Face and Expression Recognition (7 papers), Tensor decomposition and applications (7 papers), Anomaly Detection Techniques and Applications (7 papers) and Complex Network Analysis Techniques (7 papers). The work is most often cited by research in Computational Mathematics (81 citations), Computer Vision and Pattern Recognition (1.5k citations), Health Informatics (60 citations), Artificial Intelligence (1.4k citations) and Signal Processing (335 citations). Wei Peng has collaborated with scholars based in United States, China and Finland. Frequent co-authors include Tao Li, Chris Ding, Guoying Zhao, Haesun Park, Xiaopeng Hong, Elke A. Rundensteiner, Matthew O. Ward, Haoyu Chen, Zabir Al Nazi and Zitong Yu. Their work appears in journals such as Scientific Reports, IEEE Transactions on Multimedia, IEEE Transactions on Affective Computing, Pattern Recognition and Resources Conservation and Recycling.
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.