Da-Wei Jaw
Impact in
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- Image Enhancement Techniques
- Advanced Neural Network Applications
- Video Surveillance and Tracking Methods
- Advanced Image Processing Techniques
- Advanced Image and Video Retrieval Techniques
- Image and Signal Denoising Methods
- Media Technology top 5%
- Advanced Image Fusion Techniques
Papers in
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- Image Enhancement Techniques 9
- Advanced Neural Network Applications 7
- Video Surveillance and Tracking Methods 3
- Visual Attention and Saliency Detection 2
- Advanced Vision and Imaging 2
- Advanced Image Processing Techniques 2
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- Fire Detection and Safety Systems 2
- Co-authors
- Shih-Chia Huang (8 shared papers)Trung-Hieu Le (4 shared papers)Sy‐Yen Kuo (6 shared papers)Bo‐Hao Chen (3 shared papers)Shih‐Chia Huang (2 shared papers)Huibin Liu (1 shared paper)Zhihui Lu (2 shared papers)Ching-Chun Huang (1 shared paper)
In The Last Decade
Da-Wei Jaw
11 papers receiving 343 citations
Peers
Comparison fields: 5 of 53
- Computer Vision and Pattern Recognition 294
- Media Technology 60
- Safety, Risk, Reliability and Quality 39
- Human-Computer Interaction 13
- Computer Graphics and Computer-Aided Design 5
Countries citing papers authored by Da-Wei Jaw
This map shows the geographic impact of Da-Wei Jaw'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 Da-Wei Jaw with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Da-Wei Jaw more than expected).
Fields of papers citing papers by Da-Wei Jaw
This network shows the impact of papers produced by Da-Wei Jaw. 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 Da-Wei Jaw. The network helps show where Da-Wei Jaw may publish in the future.
Co-authors
The 10 scholars most cited alongside Da-Wei Jaw, 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 | 2020 | 192 | |
| 2 | 2020 | 63 | |
| 3 | 2019 | 23 | |
| 4 | 2018 | 17 | |
| 5 | 2023 | 17 | |
| 6 | 2020 | 14 | |
| 7 | 2019 | 7 | |
| 8 | 2022 | 6 | |
| 9 | 2023 | 5 | |
| 10 | 2021 | 3 | |
| 11 | 2023 | 3 |
About Da-Wei Jaw
Da-Wei Jaw is a scholar working on Computer Vision and Pattern Recognition, Safety, Risk, Reliability and Quality, Human-Computer Interaction, Media Technology and Atmospheric Science, having authored 11 papers that have together received 350 indexed citations. Recurring topics across this work include Image Enhancement Techniques (9 papers), Advanced Neural Network Applications (7 papers), Video Surveillance and Tracking Methods (3 papers), Hand Gesture Recognition Systems (2 papers), Fire Detection and Safety Systems (2 papers), Visual Attention and Saliency Detection (2 papers), Advanced Vision and Imaging (2 papers) and Advanced Image Processing Techniques (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (294 citations), Media Technology (60 citations), Safety, Risk, Reliability and Quality (39 citations), Human-Computer Interaction (13 citations) and Computer Graphics and Computer-Aided Design (5 citations). Da-Wei Jaw has collaborated with scholars based in Taiwan, Vietnam and China. Frequent co-authors include Shih-Chia Huang, Trung-Hieu Le, Sy‐Yen Kuo, Bo‐Hao Chen, Shih‐Chia Huang, Huibin Liu, Zhihui Lu, Ching-Chun Huang, Benjamin C. M. Fung and Cheng Zhang. Their work appears in journals such as IEEE Sensors Journal, ACM Transactions on Intelligent Systems and Technology, IEEE Transactions on Emerging Topics in Computing, IEEE Access and IEEE Transactions on Cybernetics.
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.