Mo Yu

1.3k citations
35 papers · 655 · 1 hit paper · h-index 10

Impact in

Papers in

Mo Yu

31 papers receiving 637 citations

Mo Yu's Hit Papers

Remaining useful life estimation via transformer encoder enhanced by a gated convolutional unit 2021 · 197 citations
1970+1+3Years since publication50100150

Peers

Mo Yu
Comparison fields: 5 of 107
  • Media Technology 115
  • Medical Laboratory Technology 18
  • Computer Vision and Pattern Recognition 229
  • Control and Systems Engineering 167
  • Safety, Risk, Reliability and Quality 50
Replace Aihua Li with:
Aihua Li China
Cunbao Ma China
Jonghyun Kim South Korea
Ting Rui China
Ruixuan Cong China
Zhenglong Cui China
Weiming Wang China
Penghui Zhao China
Mo Yu relative to Aihua Li China Aihua Li's profile →
Citations per field
00.5×3.6×
Aihua Li · 1×
Citations per year

Countries citing papers authored by Mo Yu

Since Specialization
Citations

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

Fields of papers citing papers by Mo Yu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 35 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Remaining useful life estimation via transformer encoder enhanced by a gated convolutional unit
Hit paper breakdown →
2021197
2 2018156
3
Dilated Recurrent Neural Networks
201766
4 202241
5 202129
6 202227
7 202023
8 202220
9 201815
10 202414
11 20238
12 20247
13 20236
14 20225
15 20224
16 20234
17 20243
18 20243
19 20243
20 20243

About Mo Yu

Mo Yu is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Electrical and Electronic Engineering, Control and Systems Engineering and Animal Science and Zoology, having authored 35 papers that have together received 655 indexed citations. Recurring topics across this work include Topic Modeling (9 papers), Natural Language Processing Techniques (6 papers), Advanced Vision and Imaging (5 papers), Advanced Image Processing Techniques (4 papers), Animal Nutrition and Physiology (3 papers), Fault Detection and Control Systems (3 papers), Machine Fault Diagnosis Techniques (3 papers) and Anomaly Detection Techniques and Applications (3 papers). The work is most often cited by research in Media Technology (115 citations), Medical Laboratory Technology (18 citations), Computer Vision and Pattern Recognition (229 citations), Control and Systems Engineering (167 citations) and Safety, Risk, Reliability and Quality (50 citations). Mo Yu has collaborated with scholars based in China, United States and France. Frequent co-authors include Biqing Huang, Xiu Li, Qianhui Wu, Shiyu Chang, Wei Han, Thomas S. Huang, Michael Witbrock, Ding Liu, Liang Li and Jungang Yang. Their work appears in journals such as Poultry Science, Journal of Intelligent Manufacturing, IEEE Access, Materials & Design and Advanced Engineering Informatics.

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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