Jun Chang

564 citations
106 papers · 409 · h-index 11

Impact in

Papers in

Jun Chang

83 papers receiving 376 citations

Peers

Jun Chang
Comparison fields: 5 of 74
  • Surfaces, Coatings and Films 43
  • Media Technology 53
  • Earth-Surface Processes 29
  • Computer Vision and Pattern Recognition 84
  • Biomedical Engineering 154
Replace Philip Laven with:
Philip Laven United Kingdom
Alex J. Yuffa United States
Kristan P. Gurton United States
J. Y. Wang United States
Xiang’e Han China
Bingyi Liu China
H. T. Chuah Malaysia
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Citations per field
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Citations per year

Countries citing papers authored by Jun Chang

Since Specialization
Citations

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

Fields of papers citing papers by Jun Chang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 106 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200437
2 202025
3
Dynamic Monitoring of Coastline in the Yellow River Delta by Remote Sensing
200418
4 200916
5 201515
6 201013
7 202412
8 202011
9 200911
10 201911
11 201910
12 202310
13 20159
14 20199
15 20209
16 20208
17 20178
18 20207
19 20206
20 20126

About Jun Chang

Jun Chang is a scholar working on Biomedical Engineering, Electrical and Electronic Engineering, Atomic and Molecular Physics, and Optics, Computer Vision and Pattern Recognition and Aerospace Engineering, having authored 106 papers that have together received 409 indexed citations. Recurring topics across this work include Advanced optical system design (32 papers), Adaptive optics and wavefront sensing (20 papers), Optical Systems and Laser Technology (19 papers), Infrared Target Detection Methodologies (14 papers), Optical measurement and interference techniques (13 papers), Optical Polarization and Ellipsometry (12 papers), Optical Coatings and Gratings (11 papers) and Chaos-based Image/Signal Encryption (8 papers). The work is most often cited by research in Surfaces, Coatings and Films (43 citations), Media Technology (53 citations), Earth-Surface Processes (29 citations), Computer Vision and Pattern Recognition (84 citations) and Biomedical Engineering (154 citations). Jun Chang has collaborated with scholars based in China, United States and Singapore. Frequent co-authors include Yongtian Wang, Dewen Cheng, Yongtian Wang, Gaohuan Liu, Kegen Yu, Jinwei Bu, Yongchao Zhu, Qingshen Liu, Shenliang Chen and Shupeng Chen. Their work appears in journals such as Optik, Optics Express, Optics Communications, Optics & Laser Technology and Chinese Optics 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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