En Fan

1.5k citations
44 papers · 1.0k · 1 hit paper · h-index 11

Impact in

Papers in

En Fan

39 papers receiving 990 citations

En Fan's Hit Papers

Comparative analysis of image classification algorithms based on traditional machine learning and deep learning 2020 · 541 citations
5410+2+4Years since publication100200300400500

Peers

En Fan
Comparison fields: 5 of 145
  • Computer Vision and Pattern Recognition 239
  • Media Technology 88
  • Artificial Intelligence 274
  • Signal Processing 72
  • Computer Networks and Communications 149
Replace Jaroslav Frnda with:
Jaroslav Frnda Slovakia
Kirit Modi India
Tehmina Khalil Pakistan
Rupesh Gupta India
Khushnood Abbas China
Jiwen Dong China
Brian C. Van Essen United States
Kewen Xia China
Vahid Behbood Australia
Chirag Patel India
En Fan relative to Jaroslav Frnda Slovakia Jaroslav Frnda's profile →
Citations per field
00.5×1.5×
Jaroslav Frnda · 1×
Citations per year

Countries citing papers authored by En Fan

Since Specialization
Citations

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

Fields of papers citing papers by En Fan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 44 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Comparative analysis of image classification algorithms based on traditional machine learning and deep learning
Hit paper breakdown →
2020541
2 2018100
3 201769
4 202045
5 202436
6 201730
7 201624
8 202122
9 201819
10 201915
11 201614
12 202310
13 20189
14 20148
15 20237
16 20187
17 20206
18 20175
19 20185
20 20255

About En Fan

En Fan is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Media Technology, Management Science and Operations Research and Electrical and Electronic Engineering, having authored 44 papers that have together received 1.0k indexed citations. Recurring topics across this work include Target Tracking and Data Fusion in Sensor Networks (13 papers), Multi-Criteria Decision Making (7 papers), Video Surveillance and Tracking Methods (7 papers), Maritime Navigation and Safety (5 papers), Advanced Measurement and Detection Methods (5 papers), Remote-Sensing Image Classification (4 papers), Image Enhancement Techniques (4 papers) and Optimization and Mathematical Programming (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (239 citations), Media Technology (88 citations), Artificial Intelligence (274 citations), Signal Processing (72 citations) and Computer Networks and Communications (149 citations). En Fan has collaborated with scholars based in China, Slovenia and Australia. Frequent co-authors include Pin Wang, Peng Wang, Shigen Shen, Keli Hu, Longjun Huang, Qiying Cao, Jun Ye, Shui Yu, Haiping Zhou and Jian Hua Liu. Their work appears in journals such as Journal of Intelligent & Fuzzy Systems, IEEE Access, Pattern Recognition Letters, IEEE Transactions on Fuzzy Systems and Scientific Reports.

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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