Zezhou Cheng
- Computer Vision and Pattern Recognition top 2%
- Media Technology top 5%
- Artificial Intelligence
- Computer Graphics and Computer-Aided Design top 5%
- Radiology, Nuclear Medicine and Imaging
- Co-authors
- Qingxiong YangBin ShengSubhransu MajiDaniel SheldonMatheus GadelhaJong-Chyi SuOindrila SahaCarlos Esteves
- Topics
- Advanced Image and Video Retrieval Techniques (4 papers)Domain Adaptation and Few-Shot Learning (4 papers)Advanced Neural Network Applications (3 papers)
- Cited by
- Computer Vision and Pattern RecognitionMedia TechnologyComputer Graphics and Computer-Aided Design
- Partner nations
- United StatesHong KongChina
In The Last Decade
Zezhou Cheng
14 papers receiving 521 citations
Hit Papers
Peers
Comparison fields: 5 of 75
- Computer Vision and Pattern Recognition 415
- Media Technology 93
- Artificial Intelligence 57
- Computer Graphics and Computer-Aided Design 32
- Radiology, Nuclear Medicine and Imaging 30
Countries citing papers authored by Zezhou Cheng
This map shows the geographic impact of Zezhou Cheng'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 Zezhou Cheng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Zezhou Cheng more than expected).
Fields of papers citing papers by Zezhou Cheng
This network shows the impact of papers produced by Zezhou Cheng. 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 Zezhou Cheng. The network helps show where Zezhou Cheng may publish in the future.
Co-authorship network of co-authors of Zezhou Cheng
This figure shows the co-authorship network connecting the top 25 collaborators of Zezhou Cheng. A scholar is included among the top collaborators of Zezhou Cheng 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 Zezhou Cheng. Zezhou Cheng 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 | 6 | |
| 3 | 2 | |
| 4 | 4 | |
| 5 | 7 | |
| 6 | 16 | |
| 7 | 0 | |
| 8 | 9 | |
| 9 | 9 | |
| 10 | 9 | |
| 11 | 23 | |
| 12 | Unsupervised Discovery of Object Landmarks via Contrastive Learning | 3 |
| 13 | 12 | |
| 14 | 73 | |
| 15 | 28 | |
| 16 | Deep Colorizationbreakdown → | 339 |
About Zezhou Cheng
Zezhou Cheng is a scholar working on Ecological Modeling, Computer Vision and Pattern Recognition and Artificial Intelligence, having authored 16 papers that have together received 540 indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (4 papers), Domain Adaptation and Few-Shot Learning (4 papers) and Advanced Neural Network Applications (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (415 citations), Media Technology (93 citations) and Computer Graphics and Computer-Aided Design (32 citations). Zezhou Cheng has collaborated with scholars based in United States, Hong Kong and China. Frequent co-authors include Qingxiong Yang, Bin Sheng, Subhransu Maji, Daniel Sheldon, Matheus Gadelha, Jong-Chyi Su, Bin Sheng, Oindrila Saha, Carlos Esteves and Abhishek Kar. Their work appears in journals such as Journal of Materials Chemistry A, Global Change Biology and IEEE Transactions on Image Processing.
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.