Mingyang Wu

33 papers receiving 891 citations

Mingyang Wu's Hit Papers

Depthwise separable convolution architectures for plant disease classification 2019 · 241 citations
2410+2+4Years since publication50100150200

Peers

Mingyang Wu
Comparison fields: 5 of 110
  • Signal Processing 181
  • Analytical Chemistry 92
  • Building and Construction 109
  • Computer Vision and Pattern Recognition 133
  • Health Informatics 8
Replace Kazi Md. Rokibul Alam with:
Kazi Md. Rokibul Alam Bangladesh
Reem Alkanhel Saudi Arabia
Shuteng Niu United States
S. Sumathi India
Chirag Patel India
Xinjiang Lu China
Jiangang Lu China
Baihai Zhang China
Bassant Selim Canada
Mingyang Wu relative to Kazi Md. Rokibul Alam Bangladesh Kazi Md. Rokibul Alam's profile →
Citations per field
00.5×3.1×
Kazi Md. Rokibul Alam · 1×
Citations per year

Countries citing papers authored by Mingyang Wu

Since Specialization
Citations

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

Fields of papers citing papers by Mingyang Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 39 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Depthwise separable convolution architectures for plant disease classification
Hit paper breakdown →
2019241
2 1998215
3 2006148
4 200480
5 202170
6 202241
7 202023
8 201919
9 200617
10 200111
11 20199
12 20068
13 20208
14 20177
15 20057
16 20246
17 20066
18 20195
19 20215
20 20254

About Mingyang Wu

Mingyang Wu is a scholar working on Electrical and Electronic Engineering, Computer Vision and Pattern Recognition, Signal Processing, Aerospace Engineering and Artificial Intelligence, having authored 39 papers that have together received 951 indexed citations. Recurring topics across this work include Ultra-Wideband Communications Technology (6 papers), Human Pose and Action Recognition (5 papers), Blind Source Separation Techniques (5 papers), Indoor and Outdoor Localization Technologies (5 papers), Advanced Adaptive Filtering Techniques (4 papers), Antenna Design and Analysis (4 papers), Speech and Audio Processing (4 papers) and Human Motion and Animation (3 papers). The work is most often cited by research in Signal Processing (181 citations), Analytical Chemistry (92 citations), Building and Construction (109 citations), Computer Vision and Pattern Recognition (133 citations) and Health Informatics (8 citations). Mingyang Wu has collaborated with scholars based in China, United States and Taiwan. Frequent co-authors include Hojjat Adeli, Zhendong Yin, Zhilu Wu, DeLiang Wang, Chih‐Yi Chiu, Shi-Nine Yang, Hsin-Chih Lin, Zhilu Wu, Fan‐Yi Meng and Qing Yang Steve Wu. Their work appears in journals such as Journal of Visual Communication and Image Representation, IEEE Access, Wireless Networks, Biosensors and Bioelectronics and IEEE Transactions on Audio Speech and Language Processing.

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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