Junlin Han
Impact in
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- Image Enhancement Techniques
- Advanced Image Processing Techniques
- Image and Signal Denoising Methods
- Generative Adversarial Networks and Image Synthesis
- Advanced Vision and Imaging
- Multimodal Machine Learning Applications
- Media Technology top 5%
- Advanced Image Fusion Techniques
Papers in
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- Image Enhancement Techniques 3
- Advanced Image Processing Techniques 3
- Image and Signal Denoising Methods 2
- Generative Adversarial Networks and Image Synthesis 2
- Advanced Vision and Imaging 1
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- Cancer-related molecular mechanisms research 2
- Co-authors
- Lars Petersson (5 shared papers)Mohammad Ali Armin (4 shared papers)Mehrdad Shoeiby (3 shared papers)Elizabeth Botha (2 shared papers)Janet Anstee (2 shared papers)Tim Malthus (2 shared papers)Ran Wei (2 shared papers)Saeed Anwar (2 shared papers)
- Partner nations
- AustraliaUnited StatesUnited Kingdom
In The Last Decade
Junlin Han
6 papers receiving 321 citations
Peers
Comparison fields: 5 of 51
- Computer Vision and Pattern Recognition 268
- Media Technology 62
- Computer Graphics and Computer-Aided Design 15
- Acoustics and Ultrasonics 3
- Oceanography 14
Countries citing papers authored by Junlin Han
This map shows the geographic impact of Junlin Han'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 Junlin Han with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Junlin Han more than expected).
Fields of papers citing papers by Junlin Han
This network shows the impact of papers produced by Junlin Han. 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 Junlin Han. The network helps show where Junlin Han may publish in the future.
Co-authors
The 15 scholars most cited alongside Junlin Han, 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 | 2021 | 153 | |
| 2 | 2022 | 74 | |
| 3 | 2021 | 53 | |
| 4 | 2022 | 24 | |
| 5 | 2024 | 11 | |
| 6 | 2023 | 11 |
About Junlin Han
Junlin Han is a scholar working on Computer Vision and Pattern Recognition, Cancer Research, Signal Processing, Computational Mechanics and Artificial Intelligence, having authored 6 papers that have together received 326 indexed citations. Recurring topics across this work include Image Enhancement Techniques (3 papers), Advanced Image Processing Techniques (3 papers), Image and Signal Denoising Methods (2 papers), Generative Adversarial Networks and Image Synthesis (2 papers), Cancer-related molecular mechanisms research (2 papers), Music and Audio Processing (1 paper), Speech and Audio Processing (1 paper) and Advanced Vision and Imaging (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (268 citations), Media Technology (62 citations), Computer Graphics and Computer-Aided Design (15 citations), Acoustics and Ultrasonics (3 citations) and Oceanography (14 citations). Junlin Han has collaborated with scholars based in Australia, United States and United Kingdom. Frequent co-authors include Lars Petersson, Mohammad Ali Armin, Mehrdad Shoeiby, Elizabeth Botha, Janet Anstee, Tim Malthus, Ran Wei, Saeed Anwar, Hongdong Li and Pengfei Fang. Their work appears in journals such as Remote Sensing and Lecture notes in computer science.
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.