Pin Wang
Impact in
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- Digital Imaging for Blood Diseases
- Artificial Intelligence top 2%
- AI in cancer detection
- Anomaly Detection Techniques and Applications
Papers in
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- AI in cancer detection 14
- Anomaly Detection Techniques and Applications 8
- Imbalanced Data Classification Techniques 7
- Speech Recognition and Synthesis 7
- Co-authors
- En Fan (4 shared papers)Peng Wang (2 shared papers)Yongming Li (60 shared papers)Xianling Hu (3 shared papers)Mingfeng Jiang (11 shared papers)Qianqian Liu (1 shared paper)Jiaxin Wang (5 shared papers)Song Qi (3 shared papers)
- Journals
- Biomedical Signal Processing and Control (10 papers)BioMedical Engineering OnLine (5 papers)IEEE Access (5 papers)Applied Intelligence (3 papers)Pattern Recognition Letters (2 papers)
- Partner nations
- ChinaUnited StatesUnited Kingdom
In The Last Decade
Pin Wang
154 papers receiving 2.5k citations
Pin Wang's Hit Papers
Peers
Comparison fields: 5 of 192
- Computer Vision and Pattern Recognition 590
- Artificial Intelligence 880
- Radiology, Nuclear Medicine and Imaging 433
- Biophysics 116
- Neurology 135
Countries citing papers authored by Pin Wang
This map shows the geographic impact of Pin Wang'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 Pin Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pin Wang more than expected).
Fields of papers citing papers by Pin Wang
This network shows the impact of papers produced by Pin Wang. 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 Pin Wang. The network helps show where Pin Wang may publish in the future.
Co-authors
The 25 scholars most cited alongside Pin Wang, 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 181 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Comparative analysis of image classification algorithms based on traditional machine learning and deep learning Hit paper breakdown → | 2020 | 571 |
| 2 | 2015 | 221 | |
| 3 | 2020 | 127 | |
| 4 | 2018 | 103 | |
| 5 | 2021 | 79 | |
| 6 | 2010 | 57 | |
| 7 | 2020 | 54 | |
| 8 | 2016 | 48 | |
| 9 | 2019 | 48 | |
| 10 | 2020 | 47 | |
| 11 | 2021 | 44 | |
| 12 | 2020 | 41 | |
| 13 | 2020 | 34 | |
| 14 | 2015 | 33 | |
| 15 | 2021 | 32 | |
| 16 | 2019 | 31 | |
| 17 | 2017 | 31 | |
| 18 | 2016 | 29 | |
| 19 | 2015 | 28 | |
| 20 | 2020 | 26 |
About Pin Wang
Pin Wang is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Biomedical Engineering, Radiology, Nuclear Medicine and Imaging and Physiology, having authored 181 papers that have together received 2.5k indexed citations. Recurring topics across this work include AI in cancer detection (14 papers), Voice and Speech Disorders (12 papers), Music and Audio Processing (9 papers), Anomaly Detection Techniques and Applications (8 papers), Radiomics and Machine Learning in Medical Imaging (8 papers), Imbalanced Data Classification Techniques (7 papers), Speech Recognition and Synthesis (7 papers) and Speech and Audio Processing (5 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (590 citations), Artificial Intelligence (880 citations), Radiology, Nuclear Medicine and Imaging (433 citations), Biophysics (116 citations) and Neurology (135 citations). Pin Wang has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include En Fan, Peng Wang, Yongming Li, Xianling Hu, Mingfeng Jiang, Qianqian Liu, Jiaxin Wang, Song Qi, Shanshan Lv and Yuchuan Liu. Their work appears in journals such as Biomedical Signal Processing and Control, BioMedical Engineering OnLine, IEEE Access, Applied Intelligence and Pattern Recognition Letters.
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.