Chao Du
- Computer Vision and Pattern Recognition top 10%
- Artificial Intelligence top 10%
- Information Systems
- Signal Processing
- Management Science and Operations Research
- Co-authors
- Ting ZhangJingdong WangLizhen LiuDorota KurowickaRoger CookeTianyu PangJun ZhuXinlei Zhao
- Topics
- Topic Modeling (4 papers)Natural Language Processing Techniques (4 papers)Advanced Image and Video Retrieval Techniques (4 papers)
- Journals
- IEEE Transactions on Neural Networks and Learning SystemsComputational Statistics & Data AnalysisJournal of Physics B Atomic Molecular and Optical Physics
- Partner nations
- ChinaNew ZealandNetherlands
In The Last Decade
Chao Du
32 papers receiving 253 citations
Peers
Comparison fields: 5 of 69
- Computer Vision and Pattern Recognition 132
- Artificial Intelligence 104
- Information Systems 43
- Signal Processing 21
- Management Science and Operations Research 20
Countries citing papers authored by Chao Du
This map shows the geographic impact of Chao Du'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 Chao Du with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chao Du more than expected).
Fields of papers citing papers by Chao Du
This network shows the impact of papers produced by Chao Du. 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 Chao Du. The network helps show where Chao Du may publish in the future.
Co-authorship network of co-authors of Chao Du
This figure shows the co-authorship network connecting the top 25 collaborators of Chao Du. A scholar is included among the top collaborators of Chao Du 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 Chao Du. Chao Du is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | Rethinking Softmax Cross-Entropy Loss for Adversarial Robustness | 5 |
| 3 | 3 | |
| 4 | Max-Mahalanobis Linear Discriminant Analysis Networks | 11 |
| 5 | 4 | |
| 6 | 10 | |
| 7 | 1 | |
| 8 | 3 | |
| 9 | 1 | |
| 10 | 2 | |
| 11 | 0 | |
| 12 | Robust Deep Learning via Reverse Cross-Entropy Training and Thresholding Test. | 9 |
| 13 | 3 | |
| 14 | 7 | |
| 15 | 1 | |
| 16 | 2 | |
| 17 | Composite Quantization for Approximate Nearest Neighbor Search | 109 |
| 18 | 2 | |
| 19 | 3 | |
| 20 | 31 |
About Chao Du
Chao Du is a scholar working on Artificial Intelligence, Information Systems and Computer Vision and Pattern Recognition, having authored 34 papers that have together received 268 indexed citations. Recurring topics across this work include Topic Modeling (4 papers), Natural Language Processing Techniques (4 papers) and Advanced Image and Video Retrieval Techniques (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (132 citations), Artificial Intelligence (104 citations) and Acoustics and Ultrasonics (2 citations). Chao Du has collaborated with scholars based in China, New Zealand and Netherlands. Frequent co-authors include Ting Zhang, Jingdong Wang, Lizhen Liu, Dorota Kurowicka, Roger Cooke, Tianyu Pang, Jun Zhu, Xinlei Zhao, Jun Zhu and Wei Song. Their work appears in journals such as IEEE Transactions on Neural Networks and Learning Systems, Computational Statistics & Data Analysis and Journal of Physics B Atomic Molecular and Optical Physics.
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.