Yu-Siang Wang

512 citations
12 papers · 287 · h-index 8

Impact in

    • Multimodal Machine Learning Applications
    • Advanced Image and Video Retrieval Techniques
    • Human Pose and Action Recognition
    • Topic Modeling
    • Adversarial Robustness in Machine Learning
    • Natural Language Processing Techniques
    • Domain Adaptation and Few-Shot Learning

Papers in

Yu-Siang Wang

11 papers receiving 277 citations

Peers

Yu-Siang Wang
Comparison fields: 5 of 53
  • Computer Vision and Pattern Recognition 139
  • Artificial Intelligence 167
  • Emergency Medicine 35
  • Health Informatics 3
  • Hardware and Architecture 9
Replace Xinxing Zhao with:
Xinxing Zhao Singapore
Zi Lin China
Haichuan Yang United States
Floyd M. Nolle United States
Shiyao Wang China
Meng Xing China
Dongseok Kim South Korea
Ariel Gordon United States
Himanshu Buckchash India
Yu-Siang Wang relative to Xinxing Zhao Singapore Xinxing Zhao's profile →
Citations per field
00.5×8.7×
Xinxing Zhao · 1×
Citations per year

Countries citing papers authored by Yu-Siang Wang

Since Specialization
Citations

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

Fields of papers citing papers by Yu-Siang Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yu-Siang Wang. 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 Yu-Siang Wang. The network helps show where Yu-Siang Wang may publish in the future.

Co-authors

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

All Works

12 of 12 papers shown
#Work
1 201964
2 201748
3 202137
4 201836
5 201933
6 202131
7 201819
8 202110
9 20206
10 20182
11 20211
12 20180

About Yu-Siang Wang

Yu-Siang Wang is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Information Systems, Signal Processing and Emergency Medicine, having authored 12 papers that have together received 287 indexed citations. Recurring topics across this work include Multimodal Machine Learning Applications (5 papers), Topic Modeling (4 papers), Natural Language Processing Techniques (4 papers), Human Pose and Action Recognition (3 papers), Internet Traffic Analysis and Secure E-voting (2 papers), Digital and Cyber Forensics (2 papers), Cardiac Arrest and Resuscitation (2 papers) and Advanced Malware Detection Techniques (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (139 citations), Artificial Intelligence (167 citations), Emergency Medicine (35 citations), Health Informatics (3 citations) and Hardware and Architecture (9 citations). Yu-Siang Wang has collaborated with scholars based in Taiwan, United States and Canada. Frequent co-authors include Xiaohui Zeng, Alan Yuille, Winston H. Hsu, Ya-Liang Chang, Wei-Yun Ma, Ju-Chieh Chou, Chenxi Liu, Weichao Qiu, Lingxi Xie and Yu‐Wing Tai. Their work appears in journals such as IEEE Transactions on Circuits and Systems for Video Technology, Resuscitation, Journal of Biomedical Informatics, ACM Transactions on Multimedia Computing Communications and Applications and Rare & Special e-Zone (The Hong Kong University of Science and Technology).

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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