Kunxia Wang
Impact in
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- Emotion and Mood Recognition
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- Fire Detection and Safety Systems
Papers in
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- Emotion and Mood Recognition 13
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- Face recognition and analysis 5
- Advanced Neural Network Applications 1
- Co-authors
- Yanyong Zhang (1 shared paper)Lian Li (1 shared paper)Ning An (1 shared paper)Bing Nan Li (1 shared paper)Li Liu (3 shared papers)Guoxin Su (1 shared paper)Shu Wang (1 shared paper)Jian Wang (1 shared paper)
- Journals
- IEEE Transactions on Affective Computing (3 papers)Journal of Intelligent & Fuzzy Systems (1 paper)Frontiers in Neuroscience (1 paper)IEEE Access (1 paper)Applied Intelligence (1 paper)
- Partner nations
- ChinaUnited StatesAustralia
In The Last Decade
Kunxia Wang
13 papers receiving 453 citations
Kunxia Wang's Hit Papers
Peers
Comparison fields: 5 of 34
- Experimental and Cognitive Psychology 381
- Safety, Risk, Reliability and Quality 29
- Signal Processing 15
- Artificial Intelligence 50
- Computer Vision and Pattern Recognition 32
Countries citing papers authored by Kunxia Wang
This map shows the geographic impact of Kunxia 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 Kunxia Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kunxia Wang more than expected).
Fields of papers citing papers by Kunxia Wang
This network shows the impact of papers produced by Kunxia 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 Kunxia Wang. The network helps show where Kunxia Wang may publish in the future.
Co-authors
The 18 scholars most cited alongside Kunxia 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 | Speech Emotion Recognition Using Fourier Parameters Hit paper breakdown → | 2015 | 350 |
| 2 | 2020 | 75 | |
| 3 | 2017 | 33 | |
| 4 | 2022 | 7 | |
| 5 | 2016 | 5 | |
| 6 | 2024 | 5 | |
| 7 | 2024 | 5 | |
| 8 | 2017 | 2 | |
| 9 | 2018 | 2 | |
| 10 | 2022 | 2 | |
| 11 | 2025 | 2 | |
| 12 | 2023 | 1 | |
| 13 | 2023 | 1 | |
| 14 | 2024 | 0 | |
| 15 | 2026 | 0 |
About Kunxia Wang
Kunxia Wang is a scholar working on Experimental and Cognitive Psychology, Computer Vision and Pattern Recognition, Safety, Risk, Reliability and Quality, Artificial Intelligence and Nuclear Energy and Engineering, having authored 15 papers that have together received 490 indexed citations. Recurring topics across this work include Emotion and Mood Recognition (13 papers), Face recognition and analysis (5 papers), Fire Detection and Safety Systems (1 paper), Sentiment Analysis and Opinion Mining (1 paper) and Advanced Neural Network Applications (1 paper). The work is most often cited by research in Experimental and Cognitive Psychology (381 citations), Safety, Risk, Reliability and Quality (29 citations), Signal Processing (15 citations), Artificial Intelligence (50 citations) and Computer Vision and Pattern Recognition (32 citations). Kunxia Wang has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Yanyong Zhang, Lian Li, Ning An, Bing Nan Li, Li Liu, Guoxin Su, Shu Wang, Jian Wang, Yaping He and Takashi Yamauchi. Their work appears in journals such as IEEE Transactions on Affective Computing, Journal of Intelligent & Fuzzy Systems, Frontiers in Neuroscience, IEEE Access and Applied Intelligence.
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.