Liukui Chen

27 papers receiving 409 citations

Liukui Chen's Hit Papers

AlexNet Convolutional Neural Network for Disease Detection and Classification of Tomato Leaf 2022 · 148 citations
1480+1+2Years since publication4080120

Peers

Liukui Chen
Comparison fields: 5 of 83
  • Signal Processing 88
  • Experimental and Cognitive Psychology 103
  • Analytical Chemistry 43
  • Computer Vision and Pattern Recognition 73
  • Automotive Engineering 42
Replace Pengfei Zhao with:
Pengfei Zhao China
Narit Hnoohom Thailand
Jinsoo Cho South Korea
Landu Jiang China
Kazuya Takeda Japan
Bowen Pan China
Y.S. Gan Taiwan
Juan Pablo Vásconez Chile
Liukui Chen relative to Pengfei Zhao China Pengfei Zhao's profile →
Citations per field
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Pengfei Zhao · 1×
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Countries citing papers authored by Liukui Chen

Since Specialization
Citations

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

Fields of papers citing papers by Liukui Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 32 papers — load more, or switch the sort, to bring in the rest.

#Work
1
AlexNet Convolutional Neural Network for Disease Detection and Classification of Tomato Leaf
Hit paper breakdown →
2022148
2 201773
3 202154
4 201636
5 200729
6 201924
7 201717
8 20158
9 20174
10 20174
11
Personal identification by finger vein images based on tri-value template fuzzy matching
20093
12 20233
13 20183
14 20152
15 20112
16 20142
17 20142
18 20192
19 20142
20 20182

About Liukui Chen

Liukui Chen is a scholar working on Computer Vision and Pattern Recognition, Signal Processing, Electrical and Electronic Engineering, Experimental and Cognitive Psychology and Biomedical Engineering, having authored 32 papers that have together received 429 indexed citations. Recurring topics across this work include Biometric Identification and Security (9 papers), Face and Expression Recognition (5 papers), Sleep and Work-Related Fatigue (5 papers), Vehicle emissions and performance (3 papers), Advanced Measurement and Detection Methods (3 papers), Forensic Fingerprint Detection Methods (3 papers), Image and Object Detection Techniques (3 papers) and Neural dynamics and brain function (2 papers). The work is most often cited by research in Signal Processing (88 citations), Experimental and Cognitive Psychology (103 citations), Analytical Chemistry (43 citations), Computer Vision and Pattern Recognition (73 citations) and Automotive Engineering (42 citations). Liukui Chen has collaborated with scholars based in China, New Zealand and Taiwan. Frequent co-authors include Zuojin Li, Jun Peng, Hsing‐Chung Chen, Chien‐Erh Weng, Jerry Chun‐Wei Lin, Mosiur Rahaman, Ying Wu, Simon X. Yang, Jing Wang and Haibo He. Their work appears in journals such as Sensors, Electronics, IEEE Transactions on Industrial Electronics, Human-centric Computing and Information Sciences and Applied Sciences.

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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