Long Tang

580 total citations
49 papers, 348 citations indexed

About

Long Tang is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Information Systems. According to data from OpenAlex, Long Tang has authored 49 papers receiving a total of 348 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Computer Vision and Pattern Recognition, 11 papers in Artificial Intelligence and 6 papers in Information Systems. Recurrent topics in Long Tang's work include Generative Adversarial Networks and Image Synthesis (4 papers), Face and Expression Recognition (4 papers) and Advanced Image and Video Retrieval Techniques (4 papers). Long Tang is often cited by papers focused on Generative Adversarial Networks and Image Synthesis (4 papers), Face and Expression Recognition (4 papers) and Advanced Image and Video Retrieval Techniques (4 papers). Long Tang collaborates with scholars based in China, United States and South Korea. Long Tang's co-authors include Hu Wang, G.Y. Li, Hongchao Fan, Wei Yao, James T. White, Jing Wang, Yingjie Tian, Dengpan Ye, Saiji Fu and Daqi Li and has published in prestigious journals such as Journal of Power Sources, Scientific Reports and European Journal of Operational Research.

In The Last Decade

Long Tang

45 papers receiving 335 citations

Peers

Long Tang
Comparison fields: 5 of 98
  • Computer Vision and Pattern Recognition 87
  • Artificial Intelligence 55
  • Mechanical Engineering 50
  • Computational Theory and Mathematics 48
  • Environmental Engineering 41
Replace Andreas Eichhorn with:
Andreas Eichhorn Germany
Xiaocai Zhang China
Wei Long China
Qiang Long China
Stefan Menzel Germany
Bili Chen China
Matthias Steinbrecher Germany
Fucai Qian China
Othman M. K. Alsmadi Jordan
Paola Falugi United Kingdom
Andreas Eichhorn Germany View profile →
Citations per field, relative to Long Tang
Long Tang · 1×
Citations per year, relative to Long Tang
Long Tang · 1×

Countries citing papers authored by Long Tang

Since Specialization
Citations

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

Fields of papers citing papers by Long Tang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Long Tang

This figure shows the co-authorship network connecting the top 25 collaborators of Long Tang. A scholar is included among the top collaborators of Long Tang 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 Long Tang. Long Tang 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 1
4 3
5 1
6 1
7 5
8 6
9 0
10 3
11 10
12 1
13 13
14 3
15 0
16 6
17 3
18 5
19 36
20
An MPEG-4 Motion Vector Watermarking Scheme Based on Scrambling Using Game of Life
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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