Jonathan Chan
Impact in
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- Remote-Sensing Image Classification
- Advanced Image Fusion Techniques
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- Image and Signal Denoising Methods
Papers in
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- Advanced Measurement and Detection Methods 2
- Optical Systems and Laser Technology 1
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- Remote-Sensing Image Classification 1
- Co-authors
- Jing Yang (1 shared paper)Qiang Shen (1 shared paper)Ying Li (1 shared paper)Mary L. Comer (3 shared papers)Edward J. Delp (3 shared papers)G. Furlich (2 shared papers)Irene Barbazetto (1 shared paper)Sriram Baireddy (2 shared papers)
- Journals
- Investigative Ophthalmology & Visual Science (1 paper)Remote Sensing (1 paper)IEEE Geoscience and Remote Sensing Letters (1 paper)2022 IEEE Aerospace Conference (AERO) (1 paper)
- Partner nations
- United StatesBelgiumChina
In The Last Decade
Jonathan Chan
4 papers receiving 33 citations
Peers
Comparison fields: 5 of 14
- Media Technology 17
- Computer Vision and Pattern Recognition 13
- Aerospace Engineering 14
- Atmospheric Science 4
- Electrical and Electronic Engineering 9
Countries citing papers authored by Jonathan Chan
This map shows the geographic impact of Jonathan Chan'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 Jonathan Chan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jonathan Chan more than expected).
Fields of papers citing papers by Jonathan Chan
This network shows the impact of papers produced by Jonathan Chan. 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 Jonathan Chan. The network helps show where Jonathan Chan may publish in the future.
Co-authors
The 11 scholars most cited alongside Jonathan Chan, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2017 | 19 | |
| 2 | 2022 | 11 | |
| 3 | 2021 | 2 | |
| 4 | A Method of Drusen Measurement Based on Reconstruction of Fundus Background Reflectance. | 2004 | 1 |
| 5 | 2022 | 0 |
About Jonathan Chan
Jonathan Chan is a scholar working on Electrical and Electronic Engineering, Media Technology, Aerospace Engineering, Computer Vision and Pattern Recognition and Ophthalmology, having authored 5 papers that have together received 33 indexed citations. Recurring topics across this work include Advanced Measurement and Detection Methods (2 papers), Infrared Target Detection Methodologies (2 papers), Glaucoma and retinal disorders (1 paper), Retinal Imaging and Analysis (1 paper), Optical Systems and Laser Technology (1 paper), Sparse and Compressive Sensing Techniques (1 paper), Remote-Sensing Image Classification (1 paper) and Image and Signal Denoising Methods (1 paper). The work is most often cited by research in Media Technology (17 citations), Computer Vision and Pattern Recognition (13 citations), Aerospace Engineering (14 citations), Atmospheric Science (4 citations) and Electrical and Electronic Engineering (9 citations). Jonathan Chan has collaborated with scholars based in United States, Belgium and China. Frequent co-authors include Jing Yang, Qiang Shen, Ying Li, Mary L. Comer, Edward J. Delp, G. Furlich, Irene Barbazetto, Sriram Baireddy, Janet R. Sparrow and R. Theodore Smith. Their work appears in journals such as Investigative Ophthalmology & Visual Science, Remote Sensing, IEEE Geoscience and Remote Sensing Letters and 2022 IEEE Aerospace Conference (AERO).
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.