Fei Long

412 citations
37 papers · 242 · h-index 8

Impact in

Papers in

Fei Long

35 papers receiving 228 citations

Peers

Fei Long
Comparison fields: 5 of 67
  • Computer Vision and Pattern Recognition 157
  • Experimental and Cognitive Psychology 55
  • Human-Computer Interaction 17
  • Media Technology 22
  • Urban Studies 14
Replace M. Mohamed Sathik with:
M. Mohamed Sathik India
Yangzhou Du China
Zhiqi Shen Singapore
Subhabrata Bhattacharya United States
Dongqi Cai China
Erdenebileg Batbaatar South Korea
Shiai Zhu Canada
Paraskevi Tzouveli Greece
Ayush Agarwal India
Fei Long relative to M. Mohamed Sathik India M. Mohamed Sathik's profile →
Citations per field
00.5×
M. Mohamed Sathik · 1×
Citations per year

Countries citing papers authored by Fei Long

Since Specialization
Citations

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

Fields of papers citing papers by Fei Long

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 37 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202139
2 201236
3 201826
4 201723
5 201517
6 201815
7 202015
8 202210
9
A Novel Eye Localization Method Based on Log-Gabor Transform and Integral Image
20126
10 20065
11 20195
12 20194
13 20184
14 20123
15 20143
16 20223
17 20232
18 20232
19 20172
20 20022

About Fei Long

Fei Long is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Signal Processing, Human-Computer Interaction and Cognitive Neuroscience, having authored 37 papers that have together received 242 indexed citations. Recurring topics across this work include Face and Expression Recognition (13 papers), Advanced Image and Video Retrieval Techniques (7 papers), Blind Source Separation Techniques (6 papers), Gaze Tracking and Assistive Technology (5 papers), Emotion and Mood Recognition (4 papers), EEG and Brain-Computer Interfaces (3 papers), Image Retrieval and Classification Techniques (3 papers) and Sentiment Analysis and Opinion Mining (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (157 citations), Experimental and Cognitive Psychology (55 citations), Human-Computer Interaction (17 citations), Media Technology (22 citations) and Urban Studies (14 citations). Fei Long has collaborated with scholars based in China, United States and South Korea. Frequent co-authors include Marian Stewart Bartlett, Kai Zhou, Jing-Jie Peng, Weitao Song, Jun Sang, Xiaobo Xia, Gwen Littlewort, Tingfan Wu, Javier R. Movellan and Weihua Ou. Their work appears in journals such as Neurocomputing, IEEE Access, Computer Methods and Programs in Biomedicine, Language Cognition and Neuroscience and Multimedia Tools and Applications.

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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