Ran Ju

1.2k citations
24 papers · 840 · 1 hit paper · h-index 11

Impact in

Papers in

Ran Ju

21 papers receiving 834 citations

Ran Ju's Hit Papers

Depth saliency based on anisotropic center-surround difference 2014 · 364 citations
3640+4+8Years since publication100200300

Peers

Ran Ju
Comparison fields: 5 of 68
  • Computer Vision and Pattern Recognition 621
  • Human-Computer Interaction 88
  • Sensory Systems 62
  • Media Technology 80
  • Cognitive Neuroscience 113
Replace Zhiwen Shao with:
Zhiwen Shao China
Sang-Woo Ban South Korea
Ana E. Delgado Spain
Jinxia Zhang China
Kazuhiko Kawamoto Japan
Alaa Halawani Sweden
Hong Qiao China
Chunling Fan China
Jinsoo Cho South Korea
Shenglin Mu Japan
Ran Ju relative to Zhiwen Shao China Zhiwen Shao's profile →
Citations per field
00.5×20×40×52×
Zhiwen Shao · 1×
Citations per year

Countries citing papers authored by Ran Ju

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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-authors

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.

Border = papers with Ran Ju Line = papers co-authored together Ran Ju links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 24 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Depth saliency based on anisotropic center-surround difference
Hit paper breakdown →
2014364
2 2017159
3 2015100
4 202143
5 202141
6 201724
7 201422
8 202321
9 201316
10 201513
11 201512
12 20158
13 20174
14 20144
15 20192
16 20212
17 20231
18 20201
19 20161
20 20131

About Ran Ju

Ran Ju is a scholar working on Computer Vision and Pattern Recognition, Electrical and Electronic Engineering, Computer Networks and Communications, Media Technology and Environmental Engineering, having authored 24 papers that have together received 840 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), Microbial Fuel Cells and Bioremediation (2 papers), Image Processing Techniques and Applications (2 papers) and Membrane-based Ion Separation Techniques (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (621 citations), Human-Computer Interaction (88 citations), Sensory Systems (62 citations), Media Technology (80 citations) and Cognitive Neuroscience (113 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, Tiantian Feng, Chen Ye, Junqiao Zhao, Min Zhao and Xuchun Li. Their work appears in journals such as Separation and Purification Technology, Journal of Cleaner Production, 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.

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