Chaoning Zhang
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition top 5%
- Electrical and Electronic Engineering
- Media Technology top 10%
- Signal Processing top 10%
- Co-authors
- In So KweonPhilipp BenzJean‐Charles BazinJunsik KimFrançois RameauSeokju LeeGeng SunHaiyan Lu
- Topics
- Adversarial Robustness in Machine Learning (12 papers)Domain Adaptation and Few-Shot Learning (9 papers)Privacy-Preserving Technologies in Data (8 papers)
- Partner nations
- South KoreaChinaUnited States
In The Last Decade
Chaoning Zhang
44 papers receiving 705 citations
Peers
Comparison fields: 5 of 103
- Artificial Intelligence 327
- Computer Vision and Pattern Recognition 324
- Electrical and Electronic Engineering 64
- Media Technology 50
- Signal Processing 49
Countries citing papers authored by Chaoning Zhang
This map shows the geographic impact of Chaoning Zhang'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 Chaoning Zhang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chaoning Zhang more than expected).
Fields of papers citing papers by Chaoning Zhang
This network shows the impact of papers produced by Chaoning Zhang. 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 Chaoning Zhang. The network helps show where Chaoning Zhang may publish in the future.
Co-authorship network of co-authors of Chaoning Zhang
This figure shows the co-authorship network connecting the top 25 collaborators of Chaoning Zhang. A scholar is included among the top collaborators of Chaoning Zhang 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 Chaoning Zhang. Chaoning Zhang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 0 | |
| 3 | 1 | |
| 4 | 6 | |
| 5 | 6 | |
| 6 | 3 | |
| 7 | 1 | |
| 8 | 0 | |
| 9 | 9 | |
| 10 | 1 | |
| 11 | 6 | |
| 12 | 3 | |
| 13 | 0 | |
| 14 | 24 | |
| 15 | 15 | |
| 16 | 99 | |
| 17 | 40 | |
| 18 | 68 | |
| 19 | UDH: Universal Deep Hiding for Steganography, Watermarking, and Light Field Messaging. | 67 |
| 20 | Revisiting Residual Networks with Nonlinear Shortcuts. | 13 |
About Chaoning Zhang
Chaoning Zhang is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Control and Systems Engineering, having authored 48 papers that have together received 720 indexed citations. Recurring topics across this work include Adversarial Robustness in Machine Learning (12 papers), Domain Adaptation and Few-Shot Learning (9 papers) and Privacy-Preserving Technologies in Data (8 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (324 citations), Artificial Intelligence (327 citations) and Media Technology (50 citations). Chaoning Zhang has collaborated with scholars based in South Korea, China and United States. Frequent co-authors include In So Kweon, Philipp Benz, Jean‐Charles Bazin, Junsik Kim, François Rameau, Seokju Lee, Geng Sun, Haiyan Lu, Choong Seon Hong and Simon Joss. Their work appears in journals such as Journal of Cleaner Production, Expert Systems with Applications and IEEE Access.
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.