Hui-Chuan Chen

29 papers receiving 347 citations

Peers

Hui-Chuan Chen
Comparison fields: 5 of 97
  • Artificial Intelligence 113
  • Industrial and Manufacturing Engineering 82
  • Computer Vision and Pattern Recognition 77
  • Mechanics of Materials 68
  • Mechanical Engineering 50
Replace Ernesto Bonomi with:
Ernesto Bonomi Italy
Yifan Chen United States
Feng Du China
Giuliano Laccetti Italy
Sergey Voronin Ukraine
Adam Thompson United Kingdom
Yu. G. Evtushenko Russia
Keigo Yamada Japan
Hui-Chuan Chen relative to Ernesto Bonomi Italy Ernesto Bonomi's profile →
Citations per field
00.5×5.7×
Ernesto Bonomi · 1×
Citations per year

Countries citing papers authored by Hui-Chuan Chen

Since Specialization
Citations

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

Fields of papers citing papers by Hui-Chuan Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hui-Chuan Chen

This figure shows the co-authorship network connecting the top 25 collaborators of Hui-Chuan Chen. A scholar is included among the top collaborators of Hui-Chuan Chen based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Hui-Chuan Chen. Hui-Chuan Chen is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 5
2 1
3 1
4 6
5 0
6 1
7 7
8 3
9 4
10 1
11 19
12
A New Deeper Quadtree Searchless IFS Fractal Image Encoding Method.
5
13
A New Searchless Two-Level IFS Fractal Image Encoding Method.
4
14 6
15 7
16
Fast connected component labeling algorithm using a divide and conquer technique.
50
17 68
18 38
19 19
20 48

About Hui-Chuan Chen

Hui-Chuan Chen is a scholar working on Management Information Systems, Strategy and Management and Finance, having authored 31 papers that have together received 378 indexed citations. Recurring topics across this work include Energy Load and Power Forecasting (2 papers), Reservoir Engineering and Simulation Methods (2 papers) and Advanced Data Compression Techniques (2 papers). The work is most often cited by research in Industrial and Manufacturing Engineering (82 citations), Computer Vision and Pattern Recognition (77 citations) and Artificial Intelligence (113 citations). Hui-Chuan Chen has collaborated with scholars based in United States and Taiwan. Frequent co-authors include Stéphanie Durrans, David C. Kopaska‐Merkel, Carl G. Looney, Der‐San Chen, Xianwei Wu, D. J. Jackson, Jason C. Chang, Qiang Liu, David M. Miller and Edmund Prater. Their work appears in journals such as Applied Physics Letters, IEEE Transactions on Geoscience and Remote Sensing and International Journal of Production Research.

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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