Ran Ju
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- Visual Attention and Saliency Detection 7
- Image and Video Quality Assessment 6
- Advanced Image and Video Retrieval Techniques 5
- Advanced Vision and Imaging 3
- Human-Computer Interaction top 5%
- Sensory Systems top 5%
- Media Technology top 5%
- Cognitive Neuroscience top 10%
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- Software-Defined Networks and 5G 3
- Caching and Content Delivery 2
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- Membrane-based Ion Separation Techniques 2
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- Microbial Fuel Cells and Bioremediation 2
- Co-authors
- Tongwei RenGangshan WuWenjing GengSimone MangianteYang LiuRong KangAimin HaoTiantian Feng
- Journals
- Separation and Purification Technology (2 papers)Results in Engineering (1 paper)IEEE Transactions on Intelligent Transportation Systems (1 paper)
- Partner nations
- ChinaUnited KingdomHong Kong
In The Last Decade
Ran Ju
21 papers receiving 818 citations
Hit Papers
Peers
Comparison fields: 5 of 68
- Computer Vision and Pattern Recognition 612
- Human-Computer Interaction 87
- Sensory Systems 62
- Media Technology 79
- Cognitive Neuroscience 112
Countries citing papers authored by Ran Ju
This map shows the geographic impact of Ran Ju'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 Ran Ju with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ran Ju more than expected).
Fields of papers citing papers by Ran Ju
This network shows the impact of papers produced by Ran Ju. 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 Ran Ju. The network helps show where Ran Ju may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Ran Ju, 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 | 0 | |
| 2 | 2025 | 1 | |
| 3 | 2024 | 0 | |
| 4 | 2023 | 1 | |
| 5 | 2021 | 42 | |
| 6 | 2021 | 38 | |
| 7 | 2021 | 2 | |
| 8 | 2020 | 1 | |
| 9 | 2019 | 2 | |
| 10 | 2018 | 0 | |
| 11 | 2017 | 24 | |
| 12 | 2017 | 157 | |
| 13 | 2017 | 4 | |
| 14 | 2015 | 12 | |
| 15 | 2015 | 13 | |
| 16 | 2015 | 8 | |
| 17 | Depth saliency based on anisotropic center-surround differencebreakdown → | 2014 | 355 |
| 18 | 2014 | 4 | |
| 19 | 2014 | 22 | |
| 20 | 2013 | 16 |
About Ran Ju
Ran Ju is a scholar working on Computer Vision and Pattern Recognition, Media Technology, Discrete Mathematics and Combinatorics, Algebra and Number Theory and Water Science and Technology, having authored 24 papers that have together received 824 indexed citations. Recurring topics across this work include Visual Attention and Saliency Detection (7 papers), Image and Video Quality Assessment (6 papers), Advanced Image and Video Retrieval Techniques (5 papers), Software-Defined Networks and 5G (3 papers), Advanced Vision and Imaging (3 papers), Caching and Content Delivery (2 papers), Membrane-based Ion Separation Techniques (2 papers) and Microbial Fuel Cells and Bioremediation (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (612 citations), Human-Computer Interaction (87 citations), Sensory Systems (62 citations), Media Technology (79 citations) and Cognitive Neuroscience (112 citations). Ran Ju has collaborated with scholars based in China, United Kingdom and Hong Kong. Frequent co-authors include Tongwei Ren, Gangshan Wu, Wenjing Geng, Simone Mangiante, Yang Liu, Rong Kang, Aimin Hao, Tiantian Feng, Chen Ye and Cong Chen. Their work appears in journals such as Separation and Purification Technology, Results in Engineering, IEEE Transactions on Intelligent Transportation Systems, Bioresource Technology and The Electronic Journal of Combinatorics.
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.