Jiao Dai
- Computer Vision and Pattern Recognition top 5%
- Electrical and Electronic Engineering
- Aerospace Engineering
- Renewable Energy, Sustainability and the Environment
- Artificial Intelligence
- Co-authors
- Jizhong HanZhisheng GaoGang WuSi LiuBin DongHaochen WangShitong HouJin Liu
- Topics
- Generative Adversarial Networks and Image Synthesis (18 papers)Face recognition and analysis (10 papers)Digital Media Forensic Detection (10 papers)
- Cited by
- Computer Vision and Pattern RecognitionSignal ProcessingRenewable Energy, Sustainability and the Environment
- Journals
- Angewandte Chemie International EditionSHILAP Revista de lepidopterologíaIEEE Transactions on Pattern Analysis and Machine Intelligence
- Partner nations
- ChinaPolandUnited States
In The Last Decade
Jiao Dai
64 papers receiving 593 citations
Peers
Comparison fields: 5 of 108
- Computer Vision and Pattern Recognition 214
- Electrical and Electronic Engineering 87
- Aerospace Engineering 64
- Renewable Energy, Sustainability and the Environment 64
- Artificial Intelligence 63
Countries citing papers authored by Jiao Dai
This map shows the geographic impact of Jiao Dai'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 Jiao Dai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jiao Dai more than expected).
Fields of papers citing papers by Jiao Dai
This network shows the impact of papers produced by Jiao Dai. 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 Jiao Dai. The network helps show where Jiao Dai may publish in the future.
Co-authorship network of co-authors of Jiao Dai
This figure shows the co-authorship network connecting the top 25 collaborators of Jiao Dai. A scholar is included among the top collaborators of Jiao Dai 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 Jiao Dai. Jiao Dai is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 4 | |
| 2 | 3 | |
| 3 | 1 | |
| 4 | 3 | |
| 5 | 1 | |
| 6 | 9 | |
| 7 | 23 | |
| 8 | 1 | |
| 9 | 0 | |
| 10 | 1 | |
| 11 | 2 | |
| 12 | 0 | |
| 13 | 4 | |
| 14 | 1 | |
| 15 | 8 | |
| 16 | 3 | |
| 17 | 1 | |
| 18 | 9 | |
| 19 | 2 | |
| 20 | GC Determination of Trimethyl Tin Chloride in Plastic Food Packaging Material | 1 |
About Jiao Dai
Jiao Dai is a scholar working on Computer Vision and Pattern Recognition, Catalysis and Signal Processing, having authored 73 papers that have together received 616 indexed citations. Recurring topics across this work include Generative Adversarial Networks and Image Synthesis (18 papers), Face recognition and analysis (10 papers) and Digital Media Forensic Detection (10 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (214 citations), Signal Processing (57 citations) and Renewable Energy, Sustainability and the Environment (64 citations). Jiao Dai has collaborated with scholars based in China, Poland and United States. Frequent co-authors include Jizhong Han, Zhisheng Gao, Gang Wu, Si Liu, Bin Dong, Haochen Wang, Shitong Hou, Jin Liu, Jun Wan and Weilin Xu. Their work appears in journals such as Angewandte Chemie International Edition, SHILAP Revista de lepidopterología 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.