Heng Fan
- Computer Vision and Pattern Recognition top 0.2%
- Aerospace Engineering top 1%
- Safety, Risk, Reliability and Quality top 0.5%
- Artificial Intelligence top 5%
- Global and Planetary Change top 10%
- Co-authors
- Haibin LingPeng ChuFan YangYong XuLiting LinGe DengChunyuan LiaoHexin Bai
- Topics
- Video Surveillance and Tracking Methods (34 papers)Human Pose and Action Recognition (14 papers)Advanced Neural Network Applications (12 papers)
- Cited by
- Computer Vision and Pattern RecognitionSafety, Risk, Reliability and QualityAerospace Engineering
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceIEEE Transactions on Image ProcessingIEEE Access
- Partner nations
- United StatesChinaSwitzerland
In The Last Decade
Heng Fan
61 papers receiving 3.1k citations
Hit Papers
Peers
Comparison fields: 5 of 116
- Computer Vision and Pattern Recognition 2.7k
- Aerospace Engineering 875
- Safety, Risk, Reliability and Quality 454
- Artificial Intelligence 350
- Global and Planetary Change 233
Countries citing papers authored by Heng Fan
This map shows the geographic impact of Heng Fan'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 Heng Fan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Heng Fan more than expected).
Fields of papers citing papers by Heng Fan
This network shows the impact of papers produced by Heng Fan. 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 Heng Fan. The network helps show where Heng Fan may publish in the future.
Co-authorship network of co-authors of Heng Fan
This figure shows the co-authorship network connecting the top 25 collaborators of Heng Fan. A scholar is included among the top collaborators of Heng Fan 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 Heng Fan. Heng Fan 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 | 11 | |
| 3 | 8 | |
| 4 | 6 | |
| 5 | 9 | |
| 6 | 1 | |
| 7 | 2 | |
| 8 | 3 | |
| 9 | 3 | |
| 10 | 2 | |
| 11 | ICAFusion: Iterative cross-attention guided feature fusion for multispectral object detectionbreakdown → | 137 |
| 12 | 1 | |
| 13 | 16 | |
| 14 | 2 | |
| 15 | Detection and Tracking Meet Drones Challengebreakdown → | 566 |
| 16 | 6 | |
| 17 | 21 | |
| 18 | 253 | |
| 19 | 4 | |
| 20 | 4 |
About Heng Fan
Heng Fan is a scholar working on Computer Vision and Pattern Recognition, Safety, Risk, Reliability and Quality and Artificial Intelligence, having authored 67 papers that have together received 3.1k indexed citations. Recurring topics across this work include Video Surveillance and Tracking Methods (34 papers), Human Pose and Action Recognition (14 papers) and Advanced Neural Network Applications (12 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (2.7k citations), Safety, Risk, Reliability and Quality (454 citations) and Aerospace Engineering (875 citations). Heng Fan has collaborated with scholars based in United States, China and Switzerland. Frequent co-authors include Haibin Ling, Peng Chu, Fan Yang, Yong Xu, Liting Lin, Ge Deng, Chunyuan Liao, Hexin Bai, Sijia Yu and Longyin Wen. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Image Processing 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.