Cheng Deng
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- Advanced Image and Video Retrieval Techniques 72
- Multimodal Machine Learning Applications 53
- Video Surveillance and Tracking Methods 40
- Advanced Neural Network Applications 31
- Face and Expression Recognition 27
- Human Pose and Action Recognition 25
- Image Retrieval and Classification Techniques 22
- Artificial Intelligence top 0.2%
- Domain Adaptation and Few-Shot Learning 60
- Media Technology top 0.5%
- Computational Mathematics top 5%
- Signal Processing top 2%
Cheng Deng
285 papers receiving 8.5k citations
Hit Papers
Peers
Comparison fields: 5 of 181
- Computer Vision and Pattern Recognition 6.0k
- Artificial Intelligence 3.1k
- Media Technology 633
- Computational Mathematics 23
- Signal Processing 339
Countries citing papers authored by Cheng Deng
This map shows the geographic impact of Cheng Deng'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 Cheng Deng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Cheng Deng more than expected).
Fields of papers citing papers by Cheng Deng
This network shows the impact of papers produced by Cheng Deng. 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 Cheng Deng. The network helps show where Cheng Deng may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Cheng Deng, 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 | 1 | |
| 2 | 2025 | 1 | |
| 3 | 2025 | 1 | |
| 4 | 2025 | 2 | |
| 5 | 2025 | 2 | |
| 6 | 2024 | 3 | |
| 7 | 2024 | 2 | |
| 8 | 2024 | 1 | |
| 9 | 2024 | 0 | |
| 10 | 2023 | 13 | |
| 11 | 2022 | 12 | |
| 12 | 2020 | 65 | |
| 13 | 2020 | 8 | |
| 14 | Adversarial Learning for Robust Deep Clustering | 2020 | 38 |
| 15 | Bilevel Distance Metric Learning for Robust Image Recognition | 2018 | 21 |
| 16 | Group Sparse Additive Machine | 2017 | 18 |
| 17 | Learning A Structured Optimal Bipartite Graph for Co-Clustering | 2017 | 65 |
| 18 | Tandem coexpression of CaXMT and mutants of TCS1 and analysis of enzyme activity in vitro. | 2016 | 1 |
| 19 | Multi-view matrix decomposition: a new scheme for exploring discriminative information | 2015 | 23 |
| 20 | ROCK MAGNETISM OF THE HOLOCENE EOLIAN DEPOSITS IN THE LOESS PLATEAU: EVIDENCE FOR PEDOGENESIS | 2002 | 3 |
About Cheng Deng
Cheng Deng is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Computational Mathematics, Media Technology and Computer Graphics and Computer-Aided Design, having authored 299 papers that have together received 8.6k indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (72 papers), Domain Adaptation and Few-Shot Learning (60 papers), Multimodal Machine Learning Applications (53 papers), Video Surveillance and Tracking Methods (40 papers), Advanced Neural Network Applications (31 papers), Face and Expression Recognition (27 papers), Human Pose and Action Recognition (25 papers) and Image Retrieval and Classification Techniques (22 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (6.0k citations), Artificial Intelligence (3.1k citations), Media Technology (633 citations), Computational Mathematics (23 citations) and Signal Processing (339 citations). Cheng Deng has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Dacheng Tao, Xinbo Gao, Xianglong Liu, Heng Huang, Wei Liu, Erkun Yang, Xu Yang, Xuelong Li, Tongliang Liu and Kun Wei. Their work appears in journals such as IEEE Transactions on Image Processing, IEEE Transactions on Neural Networks and Learning Systems, IEEE Transactions on Multimedia, Neurocomputing 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.