Ge-Peng Ji
- Computer Vision and Pattern Recognition top 0.2%
- Radiology, Nuclear Medicine and Imaging top 2%
- Artificial Intelligence top 2%
- Media Technology top 1%
- Aerospace Engineering top 5%
- Topics
- Visual Attention and Saliency Detection (18 papers)Advanced Image and Video Retrieval Techniques (11 papers)Image Enhancement Techniques (7 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceIEEE Transactions on Image ProcessingIEEE Transactions on Medical Imaging
- Partner nations
- ChinaUnited Arab EmiratesSwitzerland
In The Last Decade
Ge-Peng Ji
25 papers receiving 3.4k citations
Hit Papers
Peers
Comparison fields: 5 of 104
- Computer Vision and Pattern Recognition 2.6k
- Radiology, Nuclear Medicine and Imaging 724
- Artificial Intelligence 565
- Media Technology 334
- Aerospace Engineering 266
Countries citing papers authored by Ge-Peng Ji
This map shows the geographic impact of Ge-Peng Ji'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 Ge-Peng Ji with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ge-Peng Ji more than expected).
Fields of papers citing papers by Ge-Peng Ji
This network shows the impact of papers produced by Ge-Peng Ji. 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 Ge-Peng Ji. The network helps show where Ge-Peng Ji may publish in the future.
Co-authorship network of co-authors of Ge-Peng Ji
This figure shows the co-authorship network connecting the top 25 collaborators of Ge-Peng Ji. A scholar is included among the top collaborators of Ge-Peng Ji based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Ge-Peng Ji. Ge-Peng Ji is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 13 | |
| 4 | 6 | |
| 5 | 11 | |
| 6 | Deep Gradient Learning for Efficient Camouflaged Object Detectionbreakdown → | 132 |
| 7 | 13 | |
| 8 | 65 | |
| 9 | 55 | |
| 10 | Camouflaged Object Detection via Context-Aware Cross-Level Fusionbreakdown → | 141 |
| 11 | 13 | |
| 12 | Siamese Network for RGB-D Salient Object Detection and Beyondbreakdown → | 178 |
| 13 | 133 | |
| 14 | 94 | |
| 15 | Camouflaged Object Segmentation with Distraction Miningbreakdown → | 306 |
| 16 | 93 | |
| 17 | 104 | |
| 18 | Automatic Polyp Segmentation via Parallel Reverse Attention Network. | 1 |
| 19 | Inf-Net: Automatic COVID-19 Lung Infection Segmentation from CT Scans | 22 |
| 20 | JL-DCF: Joint Learning and Densely-Cooperative Fusion Framework for RGB-D Salient Object Detectionbreakdown → | 248 |
About Ge-Peng Ji
Ge-Peng Ji is a scholar working on Computer Vision and Pattern Recognition, Sensory Systems and Artificial Intelligence, having authored 28 papers that have together received 3.5k indexed citations. Recurring topics across this work include Visual Attention and Saliency Detection (18 papers), Advanced Image and Video Retrieval Techniques (11 papers) and Image Enhancement Techniques (7 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (2.6k citations), Health Informatics (92 citations) and Sensory Systems (249 citations). Ge-Peng Ji has collaborated with scholars based in China, United Arab Emirates and Switzerland. Frequent co-authors include Deng-Ping Fan, Ling Shao, Ming‐Ming Cheng, Jianbing Shen, Keren Fu, Geng Chen, Huazhu Fu, Qijun Zhao, Tao Zhou and Yi Zhou. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Image Processing and IEEE Transactions on Medical Imaging.
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.