Haotong Qin
- Computer Vision and Pattern Recognition top 2%
- Artificial Intelligence top 5%
- Electrical and Electronic Engineering
- Biomedical Engineering
- Media Technology top 5%
- Topics
- Advanced Neural Network Applications (8 papers)Domain Adaptation and Few-Shot Learning (8 papers)Anomaly Detection Techniques and Applications (6 papers)
- Journals
- SHILAP Revista de lepidopterologíaIEEE Transactions on Pattern Analysis and Machine IntelligenceThe Science of The Total Environment
- Partner nations
- ChinaSwitzerlandUnited States
In The Last Decade
Haotong Qin
27 papers receiving 1.0k citations
Hit Papers
Peers
Comparison fields: 5 of 101
- Computer Vision and Pattern Recognition 535
- Artificial Intelligence 470
- Electrical and Electronic Engineering 233
- Biomedical Engineering 76
- Media Technology 74
Countries citing papers authored by Haotong Qin
This map shows the geographic impact of Haotong Qin'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 Haotong Qin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Haotong Qin more than expected).
Fields of papers citing papers by Haotong Qin
This network shows the impact of papers produced by Haotong Qin. 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 Haotong Qin. The network helps show where Haotong Qin may publish in the future.
Co-authorship network of co-authors of Haotong Qin
This figure shows the co-authorship network connecting the top 25 collaborators of Haotong Qin. A scholar is included among the top collaborators of Haotong Qin 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 Haotong Qin. Haotong Qin is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | BiVM: Accurate Binarized Neural Network for Efficient Video Matting | 0 |
| 5 | 0 | |
| 6 | 0 | |
| 7 | 0 | |
| 8 | 0 | |
| 9 | 13 | |
| 10 | 42 | |
| 11 | 5 | |
| 12 | 0 | |
| 13 | 15 | |
| 14 | 13 | |
| 15 | 8 | |
| 16 | 8 | |
| 17 | 78 | |
| 18 | Binary neural networks: A surveybreakdown → | 325 |
| 19 | 10 | |
| 20 | IR-Net: Forward and Backward Information Retention for Highly Accurate Binary Neural Networks | 5 |
About Haotong Qin
Haotong Qin is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Hardware and Architecture, having authored 38 papers that have together received 1.1k indexed citations. Recurring topics across this work include Advanced Neural Network Applications (8 papers), Domain Adaptation and Few-Shot Learning (8 papers) and Anomaly Detection Techniques and Applications (6 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (535 citations), Artificial Intelligence (470 citations) and Media Technology (74 citations). Haotong Qin has collaborated with scholars based in China, Switzerland and United States. Frequent co-authors include Xianglong Liu, Ruihao Gong, Jingkuan Song, Nicu Sebe, Xiao Bai, Fengwei Yu, Ziran Wei, Mingzhu Shen, Xiangguo Zhang and Jiakai Wang. Their work appears in journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Pattern Analysis and Machine Intelligence and The Science of The Total Environment.
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.