Yandan Wang
Impact in
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- Advanced Neural Network Applications
- Face and Expression Recognition
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- Emotion and Mood Recognition
Papers in
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- Advanced Neural Network Applications 4
- Advanced Vision and Imaging 3
- Advanced Image and Video Retrieval Techniques 3
Yandan Wang
35 papers receiving 936 citations
Peers
Comparison fields: 5 of 110
- Computer Vision and Pattern Recognition 379
- Experimental and Cognitive Psychology 196
- Computational Mathematics 8
- Human-Computer Interaction 66
- Artificial Intelligence 332
Countries citing papers authored by Yandan Wang
This map shows the geographic impact of Yandan 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 Yandan Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yandan Wang more than expected).
Fields of papers citing papers by Yandan Wang
This network shows the impact of papers produced by Yandan 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 Yandan Wang. The network helps show where Yandan Wang may publish in the future.
Co-authors
The 25 scholars most cited alongside Yandan 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
| # | Work | ||
|---|---|---|---|
| 1 | 2024 | 4 | |
| 2 | 2023 | 2 | |
| 3 | 2023 | 7 | |
| 4 | 2023 | 4 | |
| 5 | 2022 | 8 | |
| 6 | 2022 | 12 | |
| 7 | 2021 | 12 | |
| 8 | 2021 | 2 | |
| 9 | Effects of soil nitrogen and phosphorus levels on leaf nitrogen and phosphorus contents and photosynthesis of Tamarindus indica L. in Yuanjiang and Yuanmou dryhot valley. | 2019 | 1 |
| 10 | 2019 | 35 | |
| 11 | 2018 | 119 | |
| 12 | 2018 | 17 | |
| 13 | SmoothOut: Smoothing Out Sharp Minima for Generalization in Large-Batch Deep Learning | 2018 | 0 |
| 14 | 2017 | 71 | |
| 15 | TernGrad: ternary gradients to reduce communication in distributed deep learning | 2017 | 154 |
| 16 | 2017 | 19 | |
| 17 | 2017 | 7 | |
| 18 | 2015 | 98 | |
| 19 | 2015 | 17 | |
| 20 | 1994 | 15 |
About Yandan Wang
Yandan Wang is a scholar working on Computer Vision and Pattern Recognition, Hardware and Architecture, Artificial Intelligence, Experimental and Cognitive Psychology and Signal Processing, having authored 37 papers that have together received 960 indexed citations. Recurring topics across this work include Advanced Memory and Neural Computing (6 papers), Ferroelectric and Negative Capacitance Devices (5 papers), Catalysis and Hydrodesulfurization Studies (4 papers), Emotion and Mood Recognition (4 papers), Advanced Neural Network Applications (4 papers), Nanomaterials for catalytic reactions (3 papers), Advanced Vision and Imaging (3 papers) and Advanced Image and Video Retrieval Techniques (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (379 citations), Experimental and Cognitive Psychology (196 citations), Computational Mathematics (8 citations), Human-Computer Interaction (66 citations) and Artificial Intelligence (332 citations). Yandan Wang has collaborated with scholars based in China, United States and Malaysia. Frequent co-authors include John See, Hai Li, Wei Wen, Yiran Chen, Chunpeng Wu, Raphaël C.‐W. Phan, Cong Xu, Wenbin Liu, Jing Li and Feng Yan. Their work appears in journals such as The Visual Computer, IEEE Journal on Emerging and Selected Topics in Circuits and Systems, Pattern Analysis and Applications, Food Chemistry and Catalysis Today.
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.