Maodi Hu

20 papers receiving 388 citations

Peers

Maodi Hu
Comparison fields: 5 of 46
  • Human-Computer Interaction 118
  • Computer Vision and Pattern Recognition 297
  • Biomedical Engineering 282
  • Artificial Intelligence 93
  • Signal Processing 24
Replace Edel García-Reyes with:
Edel García-Reyes Cuba
Lucas Pascotti Valem Brazil
Libin Liu Hong Kong
Tai-Peng Tian United States
Yan Ke United States
Khalid Tahboub United States
Roberto Leyva United Kingdom
Guan Luo China
Wei Qu China
Maodi Hu relative to Edel García-Reyes Cuba Edel García-Reyes's profile →
Citations per field
00.5×3.9×
Edel García-Reyes · 1×
Citations per year

Countries citing papers authored by Maodi Hu

Since Specialization
Citations

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

Fields of papers citing papers by Maodi Hu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 22 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2013103
2 201293
3 201142
4 201030
5 202124
6 200923
7 202217
8 201713
9 201212
10 20128
11 20117
12 20126
13 20235
14 20164
15 20133
16 20212
17 20242
18 20181
19 20141
20 20251

About Maodi Hu

Maodi Hu is a scholar working on Computer Vision and Pattern Recognition, Biomedical Engineering, Artificial Intelligence, Human-Computer Interaction and Statistical and Nonlinear Physics, having authored 22 papers that have together received 397 indexed citations. Recurring topics across this work include Gait Recognition and Analysis (10 papers), Human Pose and Action Recognition (9 papers), Video Surveillance and Tracking Methods (5 papers), Hand Gesture Recognition Systems (4 papers), Anomaly Detection Techniques and Applications (3 papers), Topic Modeling (3 papers), Complex Network Analysis Techniques (3 papers) and Advanced Graph Neural Networks (2 papers). The work is most often cited by research in Human-Computer Interaction (118 citations), Computer Vision and Pattern Recognition (297 citations), Biomedical Engineering (282 citations), Artificial Intelligence (93 citations) and Signal Processing (24 citations). Maodi Hu has collaborated with scholars based in China, Canada and Singapore. Frequent co-authors include Zhaoxiang Zhang, Yunhong Wang, James J. Little, Zhang De, Di Huang, Yunhong Wang, Cheng Yang, Chuan Shi, Tianchi Yang and Yunpeng Wang. Their work appears in journals such as Multimedia Tools and Applications, IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics), IEEE Transactions on Information Forensics and Security, IEEE Transactions on Cybernetics and IEEE/ACM 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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