Kuan–Chuan Peng
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence top 5%
- Cognitive Neuroscience
- Experimental and Cognitive Psychology
- Biomedical Engineering
- Topics
- Advanced Neural Network Applications (7 papers)Domain Adaptation and Few-Shot Learning (6 papers)Anomaly Detection Techniques and Applications (6 papers)
- Cited by
- Computer Vision and Pattern RecognitionArtificial IntelligenceComputer Graphics and Computer-Aided Design
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceNational University of SingaporearXiv (Cornell University)
- Partner nations
- United StatesJapanNetherlands
In The Last Decade
Kuan–Chuan Peng
19 papers receiving 435 citations
Peers
Comparison fields: 5 of 66
- Computer Vision and Pattern Recognition 325
- Artificial Intelligence 204
- Cognitive Neuroscience 73
- Experimental and Cognitive Psychology 48
- Biomedical Engineering 46
Countries citing papers authored by Kuan–Chuan Peng
This map shows the geographic impact of Kuan–Chuan 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 Kuan–Chuan Peng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kuan–Chuan Peng more than expected).
Fields of papers citing papers by Kuan–Chuan Peng
This network shows the impact of papers produced by Kuan–Chuan 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 Kuan–Chuan Peng. The network helps show where Kuan–Chuan Peng may publish in the future.
Co-authorship network of co-authors of Kuan–Chuan Peng
This figure shows the co-authorship network connecting the top 25 collaborators of Kuan–Chuan Peng. A scholar is included among the top collaborators of Kuan–Chuan Peng based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Kuan–Chuan Peng. Kuan–Chuan Peng is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 6 | |
| 3 | 1 | |
| 4 | 0 | |
| 5 | 22 | |
| 6 | 10 | |
| 7 | 1 | |
| 8 | 37 | |
| 9 | 1 | |
| 10 | 10 | |
| 11 | 43 | |
| 12 | Attention Guided Anomaly Detection and Localization in Images. | 8 |
| 13 | 16 | |
| 14 | 12 | |
| 15 | 60 | |
| 16 | 28 | |
| 17 | 157 | |
| 18 | 20 | |
| 19 | 10 | |
| 20 | 3 |
About Kuan–Chuan Peng
Kuan–Chuan Peng is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Instrumentation, having authored 21 papers that have together received 446 indexed citations. Recurring topics across this work include Advanced Neural Network Applications (7 papers), Domain Adaptation and Few-Shot Learning (6 papers) and Anomaly Detection Techniques and Applications (6 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (325 citations), Artificial Intelligence (204 citations) and Computer Graphics and Computer-Aided Design (14 citations). Kuan–Chuan Peng has collaborated with scholars based in United States, Japan and Netherlands. Frequent co-authors include Tsuhan Chen, Amir Sadovnik, Andrew Gallagher, Ziyan Wu, Lipeng Ke, Siwei Lyu, Kunpeng Li, Yun Fu, Jan Ernst and Amit K. Roy–Chowdhury. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, National University of Singapore 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.