Nan Hu

859 citations
36 papers · 608 · h-index 12

Impact in

Papers in

Nan Hu

34 papers receiving 602 citations

Peers

Nan Hu
Comparison fields: 5 of 119
  • Biological Psychiatry 98
  • Signal Processing 152
  • Computer Vision and Pattern Recognition 171
  • Behavioral Neuroscience 23
  • Computer Graphics and Computer-Aided Design 18
Replace Gang Zheng with:
Gang Zheng United States
Yuan Yuan China
Changliang Wang China
Sijia Chen China
Guofang Feng China
Dohoon Kim South Korea
Dominik Lutter Germany
Jiahong Liu China
Baohua Wu China
Dechun Wang China
Nan Hu relative to Gang Zheng United States Gang Zheng's profile →
Citations per field
00.5×10×20×30.4×
Gang Zheng · 1×
Citations per year

Countries citing papers authored by Nan Hu

Since Specialization
Citations

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

Fields of papers citing papers by Nan Hu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 36 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201783
2 202176
3 201966
4 201149
5 201545
6 201440
7 201938
8 201633
9 201427
10 202321
11 201419
12 201612
13 202210
14 201910
15 20148
16 20147
17 20157
18 20227
19 20166
20 20166

About Nan Hu

Nan Hu is a scholar working on Signal Processing, Computer Vision and Pattern Recognition, Molecular Biology, Mechanics of Materials and Pulmonary and Respiratory Medicine, having authored 36 papers that have together received 608 indexed citations. Recurring topics across this work include Video Coding and Compression Technologies (8 papers), Advanced Vision and Imaging (7 papers), Advanced Image Processing Techniques (5 papers), Composite Material Mechanics (5 papers), Bipolar Disorder and Treatment (3 papers), Advanced Mathematical Modeling in Engineering (3 papers), Advanced Data Compression Techniques (3 papers) and Tryptophan and brain disorders (3 papers). The work is most often cited by research in Biological Psychiatry (98 citations), Signal Processing (152 citations), Computer Vision and Pattern Recognition (171 citations), Behavioral Neuroscience (23 citations) and Computer Graphics and Computer-Aided Design (18 citations). Nan Hu has collaborated with scholars based in China, United States and Canada. Frequent co-authors include En‐hui Yang, Qing Yang, Dan Yang, Yang Li, Gregory F. Oxenkrug, Jacob Fish, Chunxiang Kuang, Timothy M. Chan, Jimena Berni and David Sims. Their work appears in journals such as IEEE Transactions on Circuits and Systems for Video Technology, International Journal for Numerical Methods in Engineering, eLife, Journal of Medicinal Chemistry and Medicine.

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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