Kunxia Wang

579 citations
12 papers · 435 · 1 hit paper · h-index 4

Impact in

Papers in

Kunxia Wang

10 papers receiving 413 citations

Kunxia Wang's Hit Papers

Speech Emotion Recognition Using Fourier Parameters 2015 · 315 citations
3150+3+7Years since publication100200300

Peers

Kunxia Wang
Comparison fields: 5 of 51
  • Experimental and Cognitive Psychology 303
  • Signal Processing 242
  • Pharmacy 39
  • Computer Vision and Pattern Recognition 137
  • Artificial Intelligence 127
Replace Dejan Arsić with:
Dejan Arsić Germany
Monorama Swain India
Fei Yuan China
S. Lalitha India
T. Ehrette France
Prithviraj Kabisatpathy India
Daeyoung Jang South Korea
Turgut Özseven Türkiye
Xiangju Lu China
Zhongtian Bao China
Kunxia Wang relative to Dejan Arsić Germany Dejan Arsić's profile →
Citations per field
00.5×10×15×20×25×
Dejan Arsić · 1×
Citations per year

Countries citing papers authored by Kunxia Wang

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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.

Border = papers with Kunxia Wang Line = papers co-authored together Kunxia Wang links everyone, so they are left out of the graph.

All Works

12 of 12 papers shown
#Work
1
Speech Emotion Recognition Using Fourier Parameters
Hit paper breakdown →
2015315
2 202068
3 201732
4 20226
5 20243
6 20243
7 20163
8 20183
9 20231
10 20231
11 20220
12 20250

About Kunxia Wang

Kunxia Wang is a scholar working on Experimental and Cognitive Psychology, Computer Vision and Pattern Recognition, Signal Processing, Cognitive Neuroscience and Artificial Intelligence, having authored 12 papers that have together received 435 indexed citations. Recurring topics across this work include Emotion and Mood Recognition (8 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), Advanced Text Analysis Techniques (1 paper), Fire Detection and Safety Systems (1 paper) and Face recognition and analysis (1 paper). The work is most often cited by research in Experimental and Cognitive Psychology (303 citations), Signal Processing (242 citations), Pharmacy (39 citations), Computer Vision and Pattern Recognition (137 citations) and Artificial Intelligence (127 citations). Kunxia Wang has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Lian Li, Ning An, Bing Nan Li, Yanyong Zhang, Li Liu, Guoxin Su, Shu Wang, Yaping He, Jian Wang and Takashi Yamauchi. Their work appears in journals such as Journal of Intelligent & Fuzzy Systems, IEEE Transactions on Affective Computing, 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.

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