Xia Mao

3.0k citations
120 papers · 2.4k · 1 hit paper · h-index 22

Impact in

Papers in

Xia Mao

115 papers receiving 2.3k citations

Xia Mao's Hit Papers

Speech emotion recognition using deep 1D & 2D CNN LSTM networks 2018 · 801 citations
8010+2+5Years since publication250500750

Peers

Xia Mao
Comparison fields: 5 of 132
  • Experimental and Cognitive Psychology 1.0k
  • Signal Processing 843
  • Computer Vision and Pattern Recognition 634
  • Artificial Intelligence 794
  • Pharmacy 68
Replace Zhentao Liu with:
Zhentao Liu China
Dimitrios Ververidis Greece
Ming Dong United States
Yu Tsao Taiwan
Jun Deng Germany
Margaret Lech Australia
Mark A. Clements United States
Mihalis A. Nicolaou United Kingdom
Jort F. Gemmeke Belgium
Xia Mao relative to Zhentao Liu China Zhentao Liu's profile →
Citations per field
00.5×3.0×
Zhentao Liu · 1×
Citations per year

Countries citing papers authored by Xia Mao

Since Specialization
Citations

This map shows the geographic impact of Xia Mao'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 Xia Mao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xia Mao more than expected).

Fields of papers citing papers by Xia Mao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Xia Mao. 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 Xia Mao. The network helps show where Xia Mao may publish in the future.

Co-authors

The 25 scholars most cited alongside Xia Mao, 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 Xia Mao Line = papers co-authored together Xia Mao links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 120 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Speech emotion recognition using deep 1D & 2D CNN LSTM networks
Hit paper breakdown →
2018801
2 2012186
3 2018106
4 2014101
5 201065
6 200960
7 201858
8 201750
9 201750
10 200939
11 200938
12 202137
13 201335
14 200832
15 201428
16 200627
17 201727
18 200924
19 201423
20 200823

About Xia Mao

Xia Mao is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Experimental and Cognitive Psychology, Signal Processing and Social Psychology, having authored 120 papers that have together received 2.4k indexed citations. Recurring topics across this work include Emotion and Mood Recognition (28 papers), Face and Expression Recognition (22 papers), Speech and Audio Processing (17 papers), Social Robot Interaction and HRI (14 papers), Human Pose and Action Recognition (13 papers), Infrared Target Detection Methodologies (13 papers), Speech Recognition and Synthesis (12 papers) and Advanced Measurement and Detection Methods (11 papers). The work is most often cited by research in Experimental and Cognitive Psychology (1.0k citations), Signal Processing (843 citations), Computer Vision and Pattern Recognition (634 citations), Artificial Intelligence (794 citations) and Pharmacy (68 citations). Xia Mao has collaborated with scholars based in China, Italy and Japan. Frequent co-authors include Lijiang Chen, Jianfeng Zhao, Lijiang Chen, Yuli Xue, Zheng Li, L. L. Cheng, Angelo Compare, Suzhen Yuan, Qingxu Xiong and Kang Huang. Their work appears in journals such as Multimedia Tools and Applications, Optik, The Science of The Total Environment, Neurocomputing and Electromagnetic waves.

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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