Min-Kuan Chang

570 citations
67 papers · 419 indexed · h-index 10

Min-Kuan Chang

63 papers receiving 401 citations

Peers

Min-Kuan Chang
Comparison fields: 5 of 57
  • Computer Networks and Communications 247
  • Computer Vision and Pattern Recognition 121
  • Electrical and Electronic Engineering 213
  • Media Technology 32
  • Signal Processing 33
Replace Kang Yi with:
Kang Yi South Korea
Yixiang Wang China
Andrea Marotta Italy
Chenghong Bian United Kingdom
Jean‐Pierre Cances France
Dmitry Kogan Israel
Eric Debes United States
Pietro Paglierani Italy
Min-Kuan Chang relative to Kang Yi South Korea Kang Yi's profile →
Citations per field
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Citations per year

Countries citing papers authored by Min-Kuan Chang

Since Specialization
Citations

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

Fields of papers citing papers by Min-Kuan Chang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Min-Kuan Chang. 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 Min-Kuan Chang. The network helps show where Min-Kuan Chang may publish in the future.

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20250
2 20242
3 20230
4 20206
5 20171
6 20162
7 20154
8 20154
9 20131
10
The synthesis of vertically aligned multi-walled carbon nanotube forests by thermal chemical vapor deposition
20122
11 20121
12 20113
13
Image Forgery Detection Based on Quantization Table Estimation
20091
14 20092
15 200949
16
Intrusion Detection System for Wireless Sensor Networks.
20085
17 20071
18 20072
19 200525
20 20011

About Min-Kuan Chang

Min-Kuan Chang is a scholar working on Computer Networks and Communications, Signal Processing and Computer Vision and Pattern Recognition, having authored 67 papers that have together received 419 indexed citations. Recurring topics across this work include Cooperative Communication and Network Coding (21 papers), Advanced MIMO Systems Optimization (14 papers), Wireless Communication Networks Research (11 papers), Advanced Wireless Network Optimization (9 papers), Cognitive Radio Networks and Spectrum Sensing (9 papers), Advanced Wireless Communication Techniques (8 papers), Energy Harvesting in Wireless Networks (6 papers) and Video Coding and Compression Technologies (6 papers). The work is most often cited by research in Computer Networks and Communications (247 citations), Computer Vision and Pattern Recognition (121 citations) and Electrical and Electronic Engineering (213 citations). Min-Kuan Chang has collaborated with scholars based in Taiwan, United States and China. Frequent co-authors include Guo-Shiang Lin, C.‐C. Jay Kuo, Guu-Chang Yang, Wing C. Kwong, Feng‐Tsun Chien, Wei-Chih Chen, Yitang Wang, Po-Chyi Su, Chih‐Yang Lin and Chia‐Hung Yeh. Their work appears in journals such as IEEE Transactions on Communications, IEEE Communications Letters, IEEE Transactions on Wireless Communications, Journal of Visual Communication and Image Representation and IEEE Transactions on Vehicular Technology.

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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