Kan Chang

748 citations
51 papers · 419 · h-index 12

Impact in

    • Advanced Image Fusion Techniques
    • Image Processing Techniques and Applications
    • Advanced Image Processing Techniques
    • Image and Signal Denoising Methods
    • Advanced Vision and Imaging
    • Image Enhancement Techniques

Papers in

Kan Chang

43 papers receiving 408 citations

Peers

Kan Chang
Comparison fields: 5 of 68
  • Media Technology 147
  • Computer Vision and Pattern Recognition 256
  • General Economics, Econometrics and Finance 48
  • Acoustics and Ultrasonics 3
  • Computational Mechanics 52
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Kan Chang relative to Tao Hu China Tao Hu's profile →
Citations per field
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Citations per year

Countries citing papers authored by Kan Chang

Since Specialization
Citations

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

Fields of papers citing papers by Kan Chang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 51 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200161
2 202343
3 201831
4 201829
5 202125
6 202323
7 201622
8 201520
9 201920
10 202419
11 202017
12 202411
13 201511
14 20169
15 20248
16 19888
17 20245
18 20235
19 20145
20 20135

About Kan Chang

Kan Chang is a scholar working on Computer Vision and Pattern Recognition, Signal Processing, Media Technology, Computational Mechanics and Biomedical Engineering, having authored 51 papers that have together received 419 indexed citations. Recurring topics across this work include Advanced Image Processing Techniques (19 papers), Advanced Vision and Imaging (14 papers), Video Coding and Compression Technologies (11 papers), Image and Video Quality Assessment (9 papers), Image and Signal Denoising Methods (9 papers), Image Enhancement Techniques (9 papers), Sparse and Compressive Sensing Techniques (8 papers) and Image Processing Techniques and Applications (7 papers). The work is most often cited by research in Media Technology (147 citations), Computer Vision and Pattern Recognition (256 citations), General Economics, Econometrics and Finance (48 citations), Acoustics and Ultrasonics (3 citations) and Computational Mechanics (52 citations). Kan Chang has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Baoxin Li, Wei Li, Yue Yang, Baoxin Li, Tuanfa Qin, Biao Luo, Minghong Li, Yuqian Zhao, Fan Zhang and Chunhua Yang. Their work appears in journals such as Signal Processing, Neural Networks, Signal Processing Image Communication, Expert Systems with Applications and IEEE Signal Processing Letters.

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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