Yehao Li
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- Multimodal Machine Learning Applications 20
- Human Pose and Action Recognition 13
- Advanced Image and Video Retrieval Techniques 11
- Video Analysis and Summarization 6
- Advanced Neural Network Applications 3
- Media Technology top 5%
- Artificial Intelligence top 5%
- Domain Adaptation and Few-Shot Learning 14
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- Inflammasome and immune disorders 3
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- CCD and CMOS Imaging Sensors 2
Yehao Li
33 papers receiving 1.3k citations
Hit Papers
Peers
Comparison fields: 5 of 118
- Computer Vision and Pattern Recognition 967
- Media Technology 104
- Artificial Intelligence 347
- Computer Graphics and Computer-Aided Design 27
- Industrial and Manufacturing Engineering 59
Countries citing papers authored by Yehao Li
This map shows the geographic impact of Yehao Li'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 Yehao Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yehao Li more than expected).
Fields of papers citing papers by Yehao Li
This network shows the impact of papers produced by Yehao Li. 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 Yehao Li. The network helps show where Yehao Li may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Yehao Li, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 3 | |
| 2 | 2025 | 0 | |
| 3 | 2025 | 1 | |
| 4 | 2024 | 0 | |
| 5 | 2024 | 20 | |
| 6 | 2024 | 11 | |
| 7 | 2024 | 4 | |
| 8 | 2023 | 22 | |
| 9 | 2023 | 93 | |
| 10 | 2023 | 12 | |
| 11 | 2023 | 62 | |
| 12 | 2022 | 27 | |
| 13 | 2022 | 1 | |
| 14 | 2022 | 21 | |
| 15 | Contextual Transformer Networks for Visual Recognitionbreakdown → | 2022 | 458 |
| 16 | 2022 | 8 | |
| 17 | 2022 | 1 | |
| 18 | 2021 | 37 | |
| 19 | 2019 | 11 | |
| 20 | 2018 | 110 |
About Yehao Li
Yehao Li is a scholar working on Computer Vision and Pattern Recognition, Computer Graphics and Computer-Aided Design, Artificial Intelligence, Geology and Dermatology, having authored 36 papers that have together received 1.4k indexed citations. Recurring topics across this work include Multimodal Machine Learning Applications (20 papers), Domain Adaptation and Few-Shot Learning (14 papers), Human Pose and Action Recognition (13 papers), Advanced Image and Video Retrieval Techniques (11 papers), Video Analysis and Summarization (6 papers), Advanced Neural Network Applications (3 papers), Inflammasome and immune disorders (3 papers) and CCD and CMOS Imaging Sensors (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (967 citations), Media Technology (104 citations), Artificial Intelligence (347 citations), Computer Graphics and Computer-Aided Design (27 citations) and Industrial and Manufacturing Engineering (59 citations). Yehao Li has collaborated with scholars based in China, Hong Kong and Singapore. Frequent co-authors include Ting Yao, Yingwei Pan, Tao Mei, Tao Mei, Hongyang Chao, Jingwen Chen, Yu Wang, Xiao–Ping Zhang, Chong‐Wah Ngo and Yong Rui. Their work appears in journals such as ACM Transactions on Multimedia Computing Communications and Applications, IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Multimedia, Cell Death Discovery and International Immunopharmacology.
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.