Shang-Ta Yang

402 citations
3 papers · 199 · h-index 3

Impact in

Papers in

    • Advanced Vision and Imaging 2
    • Advanced Image and Video Retrieval Techniques 1
    • Face recognition and analysis 1
    • Video Surveillance and Tracking Methods 1
    • Digital Media Forensic Detection 1
    • Biometric Identification and Security 1
Journals
King Abdullah University of Science and Technology Repository (King Abdullah University of Science and Technology) (2 papers)2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (1 paper)
Partner nations
TaiwanSaudi ArabiaCanada

In The Last Decade

Shang-Ta Yang

3 papers receiving 195 citations

Peers

Shang-Ta Yang
Comparison fields: 5 of 36
  • Signal Processing 91
  • Geology 45
  • Computer Vision and Pattern Recognition 151
  • Environmental Engineering 29
  • Aerospace Engineering 41
Replace Jared Heinly with:
Jared Heinly United States
Raghudeep Gadde Germany
Huy Tho Ho United States
Renjie Zheng China
Jan-Michael Frahm United States
Shuling Wang China
Д. В. Иванов Russia
Akio Shio Japan
Shang-Ta Yang relative to Jared Heinly United States Jared Heinly's profile →
Citations per field
00.5×
Jared Heinly · 1×
Citations per year

Countries citing papers authored by Shang-Ta Yang

Since Specialization
Citations

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

Fields of papers citing papers by Shang-Ta Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Shang-Ta Yang. 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 Shang-Ta Yang. The network helps show where Shang-Ta Yang may publish in the future.

Co-authors

The 7 scholars most cited alongside Shang-Ta Yang, 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 Shang-Ta Yang Line = papers co-authored together Shang-Ta Yang links everyone, so they are left out of the graph.

All Works

3 of 3 papers shown
#Work
1 202297
2 201997
3 20185

About Shang-Ta Yang

Shang-Ta Yang is a scholar working on Computer Vision and Pattern Recognition, Signal Processing, Environmental Engineering, Geology and Infectious Diseases, having authored 3 papers that have together received 199 indexed citations. Recurring topics across this work include Advanced Vision and Imaging (2 papers), Advanced Image and Video Retrieval Techniques (1 paper), Face recognition and analysis (1 paper), Video Surveillance and Tracking Methods (1 paper), Digital Media Forensic Detection (1 paper), Remote Sensing and LiDAR Applications (1 paper), Biometric Identification and Security (1 paper) and 3D Surveying and Cultural Heritage (1 paper). The work is most often cited by research in Signal Processing (91 citations), Geology (45 citations), Computer Vision and Pattern Recognition (151 citations), Environmental Engineering (29 citations) and Aerospace Engineering (41 citations). Shang-Ta Yang has collaborated with scholars based in Taiwan, Saudi Arabia and Canada. Frequent co-authors include Shang‐Hong Lai, Yu-Ding Lu, Hung‐Kuo Chu, Chi‐Han Peng, Peter Wonka, Min Sun and Fu-En Wang. Their work appears in journals such as King Abdullah University of Science and Technology Repository (King Abdullah University of Science and Technology) 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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