Kunxia Wang
Impact in
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- Emotion and Mood Recognition
- Signal Processing top 5%
- Speech and Audio Processing
- Music and Audio Processing
Papers in
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- Face and Expression Recognition 3
- Image Enhancement Techniques 1
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- Emotion and Mood Recognition 7
- Co-authors
- Ning An (1 shared paper)Bing Nan Li (1 shared paper)Lian Li (1 shared paper)Yanyong Zhang (1 shared paper)Li Liu (2 shared papers)Guoxin Su (1 shared paper)Shu Wang (1 shared paper)Yaping He (1 shared paper)
- Journals
- Applied Intelligence (1 paper)Neurocomputing (1 paper)IEEE Access (1 paper)IEEE Transactions on Affective Computing (1 paper)Journal of Intelligent & Fuzzy Systems (1 paper)
- Partner nations
- ChinaUnited StatesAustralia
In The Last Decade
Kunxia Wang
10 papers receiving 417 citations
Kunxia Wang's Hit Papers
Peers
Comparison fields: 5 of 51
- Experimental and Cognitive Psychology 306
- Signal Processing 242
- Pharmacy 39
- Computer Vision and Pattern Recognition 138
- Artificial Intelligence 128
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 17 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 | 315 |
| 2 | 2020 | 69 | |
| 3 | 2017 | 32 | |
| 4 | 2022 | 6 | |
| 5 | 2024 | 5 | |
| 6 | 2024 | 4 | |
| 7 | 2018 | 3 | |
| 8 | 2016 | 3 | |
| 9 | 2023 | 1 | |
| 10 | 2023 | 1 | |
| 11 | 2025 | 0 | |
| 12 | 2022 | 0 |
About Kunxia Wang
Kunxia Wang is a scholar working on Computer Vision and Pattern Recognition, Experimental and Cognitive Psychology, Signal Processing, Cognitive Neuroscience and Artificial Intelligence, having authored 12 papers that have together received 439 indexed citations. Recurring topics across this work include Emotion and Mood Recognition (7 papers), Speech and Audio Processing (4 papers), Face and Expression Recognition (3 papers), EEG and Brain-Computer Interfaces (3 papers), Gaze Tracking and Assistive Technology (2 papers), Fire Detection and Safety Systems (1 paper), Image Enhancement Techniques (1 paper) and Sentiment Analysis and Opinion Mining (1 paper). The work is most often cited by research in Experimental and Cognitive Psychology (306 citations), Signal Processing (242 citations), Pharmacy (39 citations), Computer Vision and Pattern Recognition (138 citations) and Artificial Intelligence (128 citations). Kunxia Wang has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Ning An, Bing Nan Li, Lian Li, Yanyong Zhang, Li Liu, Guoxin Su, Shu Wang, Yaping He, Jian Wang and Takashi Yamauchi. Their work appears in journals such as Applied Intelligence, Neurocomputing, IEEE Access, IEEE Transactions on Affective Computing and Journal of Intelligent & Fuzzy Systems.
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.