Shilong Wang

1.9k total citations
70 papers, 1.4k citations indexed

About

Shilong Wang is a scholar working on Industrial and Manufacturing Engineering, Computer Vision and Pattern Recognition and Computer Networks and Communications. According to data from OpenAlex, Shilong Wang has authored 70 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 31 papers in Industrial and Manufacturing Engineering, 15 papers in Computer Vision and Pattern Recognition and 13 papers in Computer Networks and Communications. Recurrent topics in Shilong Wang's work include Digital Transformation in Industry (20 papers), Manufacturing Process and Optimization (11 papers) and Scheduling and Optimization Algorithms (11 papers). Shilong Wang is often cited by papers focused on Digital Transformation in Industry (20 papers), Manufacturing Process and Optimization (11 papers) and Scheduling and Optimization Algorithms (11 papers). Shilong Wang collaborates with scholars based in China, United Kingdom and Singapore. Shilong Wang's co-authors include Bo Yang, Yankai Wang, Yang Cao, Chi Ma, Sibao Wang, Yuan Gao, Ling Kang, Jialan Liu, Tianguo Jin and Changsong Li and has published in prestigious journals such as Journal of Cleaner Production, Journal of Materials Chemistry A and Expert Systems with Applications.

In The Last Decade

Shilong Wang

64 papers receiving 1.4k citations

Peers

Shilong Wang
Comparison fields: 5 of 92
  • Industrial and Manufacturing Engineering 773
  • Mechanical Engineering 251
  • Computer Networks and Communications 204
  • Information Systems 201
  • Management of Technology and Innovation 190
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Cunbo Zhuang China View profile →
Citations per field, relative to Shilong Wang
Shilong Wang · 1×
Citations per year, relative to Shilong Wang
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Countries citing papers authored by Shilong Wang

Since Specialization
Citations

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

Fields of papers citing papers by Shilong Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shilong Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Shilong Wang. A scholar is included among the top collaborators of Shilong Wang 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 Shilong Wang. Shilong Wang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
# Work Indexed citations
1 0
2 0
3 0
4 15
5 1
6 15
7 6
8 2
9 2
10 5
11 0
12 3
13 4
14 36
15 9
16 37
17 1
18 1
19
An improved Fuzzy C-means algorithm based on gray-scale histogram for underwater image segmentation
2
20 2

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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