Ya Li
Impact in
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- Advanced Neural Network Applications
- Artificial Intelligence top 2%
- Machine Learning and Algorithms
- Domain Adaptation and Few-Shot Learning
- Adversarial Robustness in Machine Learning
- Machine Learning and Data Classification
- Anomaly Detection Techniques and Applications
- Metaheuristic Optimization Algorithms Research
Papers in
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- Adversarial Robustness in Machine Learning 4
- Advanced Computational Techniques and Applications 3
- Metaheuristic Optimization Algorithms Research 3
- Anomaly Detection Techniques and Applications 3
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- Face and Expression Recognition 3
- Video Surveillance and Tracking Methods 3
- Co-authors
- Liang Lin (4 shared papers)Dongyu Zhang (2 shared papers)Keze Wang (1 shared paper)Ruimao Zhang (1 shared paper)Guangrun Wang (2 shared papers)Qing Wang (2 shared papers)Lin Nie (2 shared papers)Wenjun Wang (1 shared paper)
In The Last Decade
Ya Li
36 papers receiving 1.1k citations
Ya Li's Hit Papers
Peers
Comparison fields: 5 of 128
- Computer Vision and Pattern Recognition 372
- Artificial Intelligence 571
- Signal Processing 87
- Media Technology 60
- Renewable Energy, Sustainability and the Environment 89
Countries citing papers authored by Ya Li
This map shows the geographic impact of Ya 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 Ya Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ya Li more than expected).
Fields of papers citing papers by Ya Li
This network shows the impact of papers produced by Ya 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 Ya Li. The network helps show where Ya Li may publish in the future.
Co-authors
The 25 scholars most cited alongside Ya 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
Showing the 20 most-cited of 44 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Cost-Effective Active Learning for Deep Image Classification Hit paper breakdown → | 2016 | 400 |
| 2 | 2017 | 151 | |
| 3 | 2018 | 132 | |
| 4 | 2019 | 92 | |
| 5 | 2020 | 91 | |
| 6 | 2020 | 54 | |
| 7 | 2020 | 34 | |
| 8 | 2020 | 29 | |
| 9 | 2016 | 24 | |
| 10 | 2014 | 23 | |
| 11 | 2015 | 19 | |
| 12 | 2020 | 14 | |
| 13 | 2019 | 12 | |
| 14 | 2022 | 11 | |
| 15 | 2020 | 9 | |
| 16 | 2024 | 8 | |
| 17 | 2011 | 4 | |
| 18 | 2024 | 3 | |
| 19 | 2012 | 3 | |
| 20 | 2024 | 2 |
About Ya Li
Ya Li is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Molecular Biology, Signal Processing and Computational Theory and Mathematics, having authored 44 papers that have together received 1.1k indexed citations. Recurring topics across this work include Adversarial Robustness in Machine Learning (4 papers), Face and Expression Recognition (3 papers), Biometric Identification and Security (3 papers), Video Surveillance and Tracking Methods (3 papers), Advanced Computational Techniques and Applications (3 papers), Medicinal Plants and Bioactive Compounds (3 papers), Metaheuristic Optimization Algorithms Research (3 papers) and Anomaly Detection Techniques and Applications (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (372 citations), Artificial Intelligence (571 citations), Signal Processing (87 citations), Media Technology (60 citations) and Renewable Energy, Sustainability and the Environment (89 citations). Ya Li has collaborated with scholars based in China, Australia and Poland. Frequent co-authors include Liang Lin, Dongyu Zhang, Keze Wang, Ruimao Zhang, Guangrun Wang, Qing Wang, Lin Nie, Wenjun Wang, Jia Zhao and Xinyu Zhou. Their work appears in journals such as The Visual Computer, Pattern Recognition, International Journal of Machine Learning and Cybernetics, Scientific Reports and Chemical Communications.
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.