Feng Han

2.8k citations
135 papers · 1.9k · 2 hit papers · h-index 19

Impact in

Papers in

Feng Han

116 papers receiving 1.8k citations

Feng Han's Hit Papers

Permutation Equivariant Graph Framelets for Heterophilous Graph Learning 2024 · 90 citations
900+2+4Years since publication100200300

Peers

Feng Han
Comparison fields: 5 of 185
  • Cognitive Neuroscience 472
  • Computer Vision and Pattern Recognition 278
  • Cellular and Molecular Neuroscience 214
  • Signal Processing 123
  • Artificial Intelligence 295
Replace Reza Ebrahimpour with:
Reza Ebrahimpour Iran
Mohammad-R. Akbarzadeh-T Iran
Valeri Mladenov Bulgaria
Yan Wu China
Alex Pappachen James Kazakhstan
Ya‐Feng Liu China
A. Prieto Spain
Zheng Tang Japan
Karim Faez Iran
K. Srinivasan India
Feng Han relative to Reza Ebrahimpour Iran Reza Ebrahimpour's profile →
Citations per field
00.5×
Reza Ebrahimpour · 1×
Citations per year

Countries citing papers authored by Feng Han

Since Specialization
Citations

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

Fields of papers citing papers by Feng Han

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 135 papers — load more, or switch the sort, to bring in the rest.

#Work
1
An Introductory Review of Deep Learning for Prediction Models With Big Data
Hit paper breakdown →
2020380
2 2008185
3 2002182
4 2005124
5 200793
6
Permutation Equivariant Graph Framelets for Heterophilous Graph Learning
Hit paper breakdown →
202490
7 200759
8 201941
9 202136
10 201636
11 202029
12 202228
13 201926
14 201923
15 202222
16 202222
17 202021
18 202219
19 202018
20 202016

About Feng Han

Feng Han is a scholar working on Artificial Intelligence, Electrical and Electronic Engineering, Computer Vision and Pattern Recognition, Control and Systems Engineering and Mechanical Engineering, having authored 135 papers that have together received 1.9k indexed citations. Recurring topics across this work include Image and Signal Denoising Methods (10 papers), Neural Networks and Applications (8 papers), Food Drying and Modeling (7 papers), Anomaly Detection Techniques and Applications (7 papers), Advanced Numerical Analysis Techniques (7 papers), Mathematical Analysis and Transform Methods (5 papers), Advanced Electrical Measurement Techniques (4 papers) and Agricultural Engineering and Mechanization (4 papers). The work is most often cited by research in Cognitive Neuroscience (472 citations), Computer Vision and Pattern Recognition (278 citations), Cellular and Molecular Neuroscience (214 citations), Signal Processing (123 citations) and Artificial Intelligence (295 citations). Feng Han has collaborated with scholars based in China, Hong Kong and United States. Frequent co-authors include Yang Dan, Frank Emmert‐Streib, Shailesh Tripathi, Zhen Yang, Matthias Dehmer, Natalia Caporale, Yeong-Khing Ho, Chin-Seng Chua, Wenfu Wu and Gidon Felsen. Their work appears in journals such as International Journal of Food Properties, IEEE Transactions on Neural Networks and Learning Systems, Foods, Analysis and Applications and Journal of Food Process Engineering.

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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