Deng Cai
- Computer Vision and Pattern Recognition top 0.05%
- Advanced Image and Video Retrieval Techniques 76
- Image Retrieval and Classification Techniques 57
- Face and Expression Recognition 55
- Multimodal Machine Learning Applications 22
- Advanced Neural Network Applications 20
- Computational Mathematics top 0.5%
- Artificial Intelligence top 0.05%
- Topic Modeling 26
- Domain Adaptation and Few-Shot Learning 18
- Media Technology top 0.1%
- Signal Processing top 0.2%
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- Sparse and Compressive Sensing Techniques 18
- Journals
- Neurocomputing (25 papers)IEEE Transactions on Knowledge and Data Engineering (18 papers)IEEE Transactions on Image Processing (17 papers)
- Partner nations
- ChinaUnited StatesUnited Kingdom
In The Last Decade
Deng Cai
224 papers receiving 15.2k citations
Hit Papers
Peers
Comparison fields: 5 of 179
- Computer Vision and Pattern Recognition 9.8k
- Computational Mathematics 241
- Artificial Intelligence 7.0k
- Media Technology 1.9k
- Signal Processing 1.4k
Countries citing papers authored by Deng Cai
This map shows the geographic impact of Deng Cai'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 Deng Cai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Deng Cai more than expected).
Fields of papers citing papers by Deng Cai
This network shows the impact of papers produced by Deng Cai. 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 Deng Cai. The network helps show where Deng Cai may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Deng Cai, 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 | 2025 | 2 | |
| 2 | 2025 | 2 | |
| 3 | 2024 | 3 | |
| 4 | 2024 | 1 | |
| 5 | 2024 | 2 | |
| 6 | 2023 | 13 | |
| 7 | 2023 | 9 | |
| 8 | 2023 | 11 | |
| 9 | 2023 | 7 | |
| 10 | 2022 | 2 | |
| 11 | 2022 | 17 | |
| 12 | 2020 | 36 | |
| 13 | 2020 | 48 | |
| 14 | 2016 | 19 | |
| 15 | Non-negative matrix factorization with sinkhorn distance | 2016 | 20 |
| 16 | Multi-Manifold Concept Factorization for Data Clustering | 2013 | 4 |
| 17 | 2013 | 37 | |
| 18 | Sparse projections over graph | 2008 | 15 |
| 19 | Laplacian Score for Feature Selectionbreakdown → | 2005 | 1321 |
| 20 | Tensor Subspace Analysis | 2005 | 276 |
About Deng Cai
Deng Cai is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Signal Processing, Media Technology and Computational Mathematics, having authored 231 papers that have together received 15.7k indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (76 papers), Image Retrieval and Classification Techniques (57 papers), Face and Expression Recognition (55 papers), Topic Modeling (26 papers), Multimodal Machine Learning Applications (22 papers), Advanced Neural Network Applications (20 papers), Sparse and Compressive Sensing Techniques (18 papers) and Domain Adaptation and Few-Shot Learning (18 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (9.8k citations), Computational Mathematics (241 citations), Artificial Intelligence (7.0k citations), Media Technology (1.9k citations) and Signal Processing (1.4k citations). Deng Cai has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Xiaofei He, Jiawei Han, Partha Niyogi, Jiawei Han, Wei‐Ying Ma, Chiyuan Zhang, Xuelong Li, Jiajun Bu, Ji-Rong Wen and Chun Chen. Their work appears in journals such as Neurocomputing, IEEE Transactions on Knowledge and Data Engineering, IEEE Transactions on Image Processing, IEEE Transactions on Cybernetics and IEEE Transactions on Pattern Analysis and Machine Intelligence.
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.