Hong-Han Shuai
- Computer Vision and Pattern Recognition top 1%
- Artificial Intelligence top 2%
- Experimental and Cognitive Psychology top 5%
- Information Systems top 5%
- Signal Processing top 5%
- Co-authors
- Ling LoWen-Huang ChengHongxia XieHao‐Wen ChengMing-Syan Chen⋆De-Nian YangPhilip S. YuJun-Cheng Chen
- Topics
- Complex Network Analysis Techniques (14 papers)Anomaly Detection Techniques and Applications (13 papers)Video Surveillance and Tracking Methods (12 papers)
- Cited by
- Computer Vision and Pattern RecognitionArtificial IntelligenceExperimental and Cognitive Psychology
- Journals
- IEEE Transactions on Geoscience and Remote SensingACM Computing SurveysIEEE Transactions on Intelligent Transportation Systems
- Partner nations
- TaiwanUnited StatesChina
In The Last Decade
Hong-Han Shuai
106 papers receiving 1.5k citations
Hit Papers
Peers
Comparison fields: 5 of 117
- Computer Vision and Pattern Recognition 745
- Artificial Intelligence 494
- Experimental and Cognitive Psychology 194
- Information Systems 138
- Signal Processing 125
Countries citing papers authored by Hong-Han Shuai
This map shows the geographic impact of Hong-Han Shuai'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 Hong-Han Shuai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hong-Han Shuai more than expected).
Fields of papers citing papers by Hong-Han Shuai
This network shows the impact of papers produced by Hong-Han Shuai. 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 Hong-Han Shuai. The network helps show where Hong-Han Shuai may publish in the future.
Co-authorship network of co-authors of Hong-Han Shuai
This figure shows the co-authorship network connecting the top 25 collaborators of Hong-Han Shuai. A scholar is included among the top collaborators of Hong-Han Shuai 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 Hong-Han Shuai. Hong-Han Shuai is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | Lightweight Deep Learning for Resource-Constrained Environments: A Surveybreakdown → | 59 |
| 3 | 1 | |
| 4 | 50 | |
| 5 | 2 | |
| 6 | 14 | |
| 7 | 5 | |
| 8 | 6 | |
| 9 | 4 | |
| 10 | 8 | |
| 11 | 81 | |
| 12 | 27 | |
| 13 | 14 | |
| 14 | 3 | |
| 15 | 39 | |
| 16 | 19 | |
| 17 | 28 | |
| 18 | 6 | |
| 19 | 19 | |
| 20 | 0 |
About Hong-Han Shuai
Hong-Han Shuai is a scholar working on Computational Mathematics, Computer Vision and Pattern Recognition and Artificial Intelligence, having authored 119 papers that have together received 1.5k indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (14 papers), Anomaly Detection Techniques and Applications (13 papers) and Video Surveillance and Tracking Methods (12 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (745 citations), Artificial Intelligence (494 citations) and Experimental and Cognitive Psychology (194 citations). Hong-Han Shuai has collaborated with scholars based in Taiwan, United States and China. Frequent co-authors include Ling Lo, Wen-Huang Cheng, Hongxia Xie, Wen-Huang Cheng, Hao‐Wen Cheng, Ming-Syan Chen⋆, De-Nian Yang, Philip S. Yu, Jun-Cheng Chen and Wang-Chien Lee. Their work appears in journals such as IEEE Transactions on Geoscience and Remote Sensing, ACM Computing Surveys and IEEE Transactions on Intelligent Transportation Systems.
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.