Cusuh Ham
Impact in
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- Advanced Image and Video Retrieval Techniques
- Multimodal Machine Learning Applications
- Image Retrieval and Classification Techniques
- Advanced Vision and Imaging
- Generative Adversarial Networks and Image Synthesis
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- Computer Graphics and Visualization Techniques
Papers in
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- Multimodal Machine Learning Applications 3
- Advanced Image and Video Retrieval Techniques 2
- Video Analysis and Summarization 1
- Image Processing and 3D Reconstruction 1
- Image Retrieval and Classification Techniques 1
- Advanced Vision and Imaging 1
- Generative Adversarial Networks and Image Synthesis 1
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- Computer Graphics and Visualization Techniques 2
- Co-authors
- James Hays (4 shared papers)Patsorn Sangkloy (1 shared paper)Jingwan Lu (2 shared papers)Krishna Kumar Singh (1 shared paper)Tobias Hinz (2 shared papers)Zhifei Zhang (1 shared paper)Amit Raj (1 shared paper)Connelly Barnes (1 shared paper)
- Journals
- ACM Transactions on Graphics (1 paper)Computer Vision and Pattern Recognition (1 paper)Monash University Research Portal (Monash University) (1 paper)
- Partner nations
- United StatesHong KongAustralia
In The Last Decade
Cusuh Ham
5 papers receiving 445 citations
Cusuh Ham's Hit Papers
Peers
Comparison fields: 5 of 38
- Computer Vision and Pattern Recognition 410
- Computer Graphics and Computer-Aided Design 55
- Geology 18
- Computational Mechanics 58
- Artificial Intelligence 95
Countries citing papers authored by Cusuh Ham
This map shows the geographic impact of Cusuh Ham'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 Cusuh Ham with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Cusuh Ham more than expected).
Fields of papers citing papers by Cusuh Ham
This network shows the impact of papers produced by Cusuh Ham. 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 Cusuh Ham. The network helps show where Cusuh Ham may publish in the future.
Co-authors
The 18 scholars most cited alongside Cusuh Ham, 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 | The sketchy database Hit paper breakdown → | 2016 | 435 |
| 2 | 2023 | 12 | |
| 3 | Learning to Generate Textures on 3D Meshes | 2019 | 3 |
| 4 | 2024 | 3 | |
| 5 | 2025 | 2 |
About Cusuh Ham
Cusuh Ham is a scholar working on Computer Vision and Pattern Recognition, Computer Graphics and Computer-Aided Design, Computational Mechanics, Media Technology and Infectious Diseases, having authored 5 papers that have together received 455 indexed citations. Recurring topics across this work include Multimodal Machine Learning Applications (3 papers), Advanced Image and Video Retrieval Techniques (2 papers), Computer Graphics and Visualization Techniques (2 papers), Video Analysis and Summarization (1 paper), Image Processing and 3D Reconstruction (1 paper), Image Retrieval and Classification Techniques (1 paper), Advanced Vision and Imaging (1 paper) and Generative Adversarial Networks and Image Synthesis (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (410 citations), Computer Graphics and Computer-Aided Design (55 citations), Geology (18 citations), Computational Mechanics (58 citations) and Artificial Intelligence (95 citations). Cusuh Ham has collaborated with scholars based in United States, Hong Kong and Australia. Frequent co-authors include James Hays, Patsorn Sangkloy, Jingwan Lu, Krishna Kumar Singh, Tobias Hinz, Zhifei Zhang, Amit Raj, Connelly Barnes, Vladimir G. Kim and Jiahui Huang. Their work appears in journals such as ACM Transactions on Graphics, Computer Vision and Pattern Recognition and Monash University Research Portal (Monash 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.