Runmin Cong
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- Visual Attention and Saliency Detection 42
- Image Enhancement Techniques 26
- Advanced Image Processing Techniques 25
- Advanced Neural Network Applications 19
- Advanced Image and Video Retrieval Techniques 19
- Advanced Vision and Imaging 18
- Image and Video Quality Assessment 10
- Media Technology top 0.05%
- Advanced Image Fusion Techniques 24
- Sensory Systems top 1%
- Human-Computer Interaction top 2%
- Cognitive Neuroscience top 5%
Runmin Cong
100 papers receiving 6.7k citations
Hit Papers
Peers
Comparison fields: 5 of 121
- Computer Vision and Pattern Recognition 6.1k
- Media Technology 2.2k
- Sensory Systems 310
- Human-Computer Interaction 194
- Cognitive Neuroscience 504
Countries citing papers authored by Runmin Cong
This map shows the geographic impact of Runmin Cong'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 Runmin Cong with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Runmin Cong more than expected).
Fields of papers citing papers by Runmin Cong
This network shows the impact of papers produced by Runmin Cong. 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 Runmin Cong. The network helps show where Runmin Cong may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Runmin Cong, 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 | 2025 | 1 | |
| 2 | 2025 | 2 | |
| 3 | 2025 | 0 | |
| 4 | 2025 | 1 | |
| 5 | 2024 | 15 | |
| 6 | 2024 | 4 | |
| 7 | 2024 | 5 | |
| 8 | 2024 | 6 | |
| 9 | 2024 | 4 | |
| 10 | 2024 | 1 | |
| 11 | 2024 | 4 | |
| 12 | PUGAN: Physical Model-Guided Underwater Image Enhancement Using GAN With Dual-Discriminatorsbreakdown → | 2023 | 162 |
| 13 | 2023 | 8 | |
| 14 | 2022 | 77 | |
| 15 | 2021 | 69 | |
| 16 | Dense Attention Fluid Network for Salient Object Detection in Optical Remote Sensing Imagesbreakdown → | 2020 | 231 |
| 17 | 2019 | 78 | |
| 18 | 2019 | 120 | |
| 19 | 2018 | 85 | |
| 20 | 2017 | 101 |
About Runmin Cong
Runmin Cong is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Sensory Systems, having authored 109 papers that have together received 6.8k indexed citations. Recurring topics across this work include Visual Attention and Saliency Detection (42 papers), Image Enhancement Techniques (26 papers), Advanced Image Processing Techniques (25 papers), Advanced Image Fusion Techniques (24 papers), Advanced Neural Network Applications (19 papers), Advanced Image and Video Retrieval Techniques (19 papers), Advanced Vision and Imaging (18 papers) and Image and Video Quality Assessment (10 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (6.1k citations), Media Technology (2.2k citations) and Sensory Systems (310 citations). Runmin Cong has collaborated with scholars based in China, Hong Kong and Singapore. Frequent co-authors include Chongyi Li, Sam Kwong, Jichang Guo, Chunle Guo, Qingming Huang, Junhui Hou, Huazhu Fu, Yao Zhao, Chen Change Loy and Jianjun Lei. Their work appears in journals such as IEEE Transactions on Image Processing, IEEE Transactions on Multimedia, IEEE Transactions on Circuits and Systems for Video Technology, IEEE Transactions on Cybernetics and IEEE Transactions on Geoscience and Remote Sensing.
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.