Shuo Wang

5.1k citations
138 papers · 3.2k indexed · 1 hit paper · h-index 29

Impact in

Papers in

Shuo Wang

120 papers receiving 3.1k citations

Hit Papers

Detect Globally, Refine Locally: A Novel Approach to Saliency Detection 2018 · 353 citations
3532018202620202023100200300

Peers

Shuo Wang
Comparison fields: 5 of 176
  • Computer Vision and Pattern Recognition 901
  • Polymers and Plastics 331
  • Artificial Intelligence 736
  • Health Informatics 25
  • Electrical and Electronic Engineering 896
Replace Mingxia Liu with:
Mingxia Liu China
Hongyan Liu China
Seung‐Chul Lee South Korea
Rizwan Ali Naqvi South Korea
Zhenhui Li China
Xinlei Chen China
Sang‐Chul Lee South Korea
Peng Yu China
Sung Won Kim South Korea
Li Xiong United States
Shuo Wang relative to Mingxia Liu China Mingxia Liu's profile →
Citations per field
00.5×3.1×
Mingxia Liu · 1×
Citations per year

Countries citing papers authored by Shuo Wang

Since Specialization
Citations

This map shows the geographic impact of Shuo Wang'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 Shuo Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shuo Wang more than expected).

Fields of papers citing papers by Shuo Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Shuo Wang. 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 Shuo Wang. The network helps show where Shuo Wang may publish in the future.

Co-authors

The 25 scholars most cited alongside Shuo Wang, 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 Shuo Wang Line = papers co-authored together Shuo Wang links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 138 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Detect Globally, Refine Locally: A Novel Approach to Saliency Detection
Hit paper breakdown →
2018353
2 2014292
3 2012223
4 2020130
5 2018115
6 2020114
7 2020113
8 2021108
9 201190
10 201789
11 202386
12 201977
13 201077
14 202068
15 201962
16 202354
17 201948
18 201940
19 202138
20 202336

About Shuo Wang

Shuo Wang is a scholar working on Computer Vision and Pattern Recognition, Polymers and Plastics, Radiology, Nuclear Medicine and Imaging, Artificial Intelligence and Health Informatics, having authored 138 papers that have together received 3.2k indexed citations. Recurring topics across this work include Perovskite Materials and Applications (27 papers), Quantum Dots Synthesis And Properties (13 papers), Conducting polymers and applications (12 papers), Chalcogenide Semiconductor Thin Films (10 papers), Advanced Neural Network Applications (9 papers), Medical Image Segmentation Techniques (8 papers), Radiomics and Machine Learning in Medical Imaging (8 papers) and AI in cancer detection (7 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (901 citations), Polymers and Plastics (331 citations), Artificial Intelligence (736 citations), Health Informatics (25 citations) and Electrical and Electronic Engineering (896 citations). Shuo Wang has collaborated with scholars based in China, United Kingdom and United States. Frequent co-authors include Xin Yao, Leandro L. Minku, Jianwu Jiang, Shuming Zhao, Huchuan Lu, Chengyan Wang, Gang Yang, Lihe Zhang, Ali Borji and Xiang Ruan. Their work appears in journals such as Medical Image Analysis, Nature Communications, Optics Express, Solar Energy and IEEE Access.

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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