Triet Le

995 citations
18 papers · 714 · h-index 10

Impact in

Papers in

Triet Le

18 papers receiving 663 citations

Peers

Triet Le
Comparison fields: 5 of 79
  • Computer Vision and Pattern Recognition 516
  • Media Technology 157
  • Mathematical Physics 99
  • Computational Mechanics 194
  • Computer Graphics and Computer-Aided Design 21
Replace Pavel Mrázek⋆ with:
Pavel Mrázek⋆ Germany
Leah Bar Israel
Andrés Solé Spain
Tanja Teuber Germany
Miyoun Jung South Korea
Luca Calatroni France
Ginmo Chung United States
Carole Le Guyader France
Xiao-Guang Lv China
Ganesh Sundaramoorthi United States
Triet Le relative to Pavel Mrázek⋆ Germany Pavel Mrázek⋆'s profile →
Citations per field
00.5×2×3×4×5×
Pavel Mrázek⋆ · 1×
Citations per year

Countries citing papers authored by Triet Le

Since Specialization
Citations

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

Fields of papers citing papers by Triet Le

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 20 scholars most cited alongside Triet Le, 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 Triet Le Line = papers co-authored together Triet Le links everyone, so they are left out of the graph.

All Works

18 of 18 papers shown
#Work
1 2007321
2 2010162
3 200560
4 200747
5 201029
6 201126
7 201215
8 201114
9 200811
10 201610
11 20065
12 20083
13 20183
14 20153
15 20252
16 20241
17 20191
18 20241

About Triet Le

Triet Le is a scholar working on Computer Vision and Pattern Recognition, Mathematical Physics, Computational Theory and Mathematics, Numerical Analysis and Control and Systems Engineering, having authored 18 papers that have together received 714 indexed citations. Recurring topics across this work include Medical Image Segmentation Techniques (6 papers), Image and Signal Denoising Methods (5 papers), Numerical methods in inverse problems (4 papers), Advanced Mathematical Modeling in Engineering (4 papers), Generative Adversarial Networks and Image Synthesis (3 papers), Mathematical Biology Tumor Growth (2 papers), Cell Image Analysis Techniques (2 papers) and Advanced Image Processing Techniques (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (516 citations), Media Technology (157 citations), Mathematical Physics (99 citations), Computational Mechanics (194 citations) and Computer Graphics and Computer-Aided Design (21 citations). Triet Le has collaborated with scholars based in United States, Vietnam and France. Frequent co-authors include Thomas J. Asaki, Rick Chartrand, Luminita A. Vese, Antoni Buades, Jean‐Michel Morel, John B. Garnett, Yves Meyer, Sung Ha Kang, Peter W. Jones and Tuan Huy Nguyen. Their work appears in journals such as Journal of Mathematical Imaging and Vision, Applied and Computational Harmonic Analysis, Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery, Pure and Applied Mathematics Quarterly and Transactions of the American Mathematical Society.

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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