Li-Chih Chen

408 citations
14 papers · 311 · h-index 8

Impact in

Papers in

Li-Chih Chen

14 papers receiving 295 citations

Peers

Li-Chih Chen
Comparison fields: 5 of 41
  • Media Technology 123
  • Computer Vision and Pattern Recognition 266
  • Automotive Engineering 64
  • Industrial and Manufacturing Engineering 27
  • Building and Construction 33
Replace Qichang Hu with:
Qichang Hu Australia
Mourad A. Kenk Egypt
Huai Yuan China
Vinh Dinh Nguyen South Korea
Jakub Špaňhel Czechia
Evair Borges Severo Brazil
Chao-Ho Chen Taiwan
Andrzej Głowacz Poland
Reza Mahjourian United States
Li-Chih Chen relative to Qichang Hu Australia Qichang Hu's profile →
Citations per field
00.5×10×15×21.5×
Qichang Hu · 1×
Citations per year

Countries citing papers authored by Li-Chih Chen

Since Specialization
Citations

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

Fields of papers citing papers by Li-Chih Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 8 scholars most cited alongside Li-Chih 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 Li-Chih Chen Line = papers co-authored together Li-Chih Chen links everyone, so they are left out of the graph.

All Works

14 of 14 papers shown
#Work
1 2014154
2 201547
3 201430
4 201017
5 201414
6 201314
7 201312
8 20158
9 20155
10 20124
11 20132
12 20142
13 20151
14 20141

About Li-Chih Chen

Li-Chih Chen is a scholar working on Computer Vision and Pattern Recognition, Ocean Engineering, Media Technology, Environmental Engineering and Electrical and Electronic Engineering, having authored 14 papers that have together received 311 indexed citations. Recurring topics across this work include Video Surveillance and Tracking Methods (13 papers), Advanced Image and Video Retrieval Techniques (5 papers), Advanced Neural Network Applications (3 papers), Remote Sensing and LiDAR Applications (2 papers), Human Pose and Action Recognition (2 papers), Spectroscopy and Chemometric Analyses (2 papers), Advanced Measurement and Detection Methods (2 papers) and Automated Road and Building Extraction (2 papers). The work is most often cited by research in Media Technology (123 citations), Computer Vision and Pattern Recognition (266 citations), Automotive Engineering (64 citations), Industrial and Manufacturing Engineering (27 citations) and Building and Construction (33 citations). Li-Chih Chen has collaborated with scholars based in Taiwan and Russia. Frequent co-authors include Duan-Yu Chen, Jun-Wei Hsieh, Jun‐Wei Hsieh, Shyi‐Chyi Cheng, Wei-Ru Lai, Shih‐Chun Lin, Tsung-Hsien Tsai and Yilin Yan. Their work appears in journals such as IEEE Sensors Journal, Journal of Visual Communication and Image Representation, Pattern Recognition and IEEE Transactions on Intelligent Transportation Systems.

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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