Prune Truong

419 citations
6 papers · 189 · h-index 5

Impact in

Papers in

Journals
IEEE Transactions on Pattern Analysis and Machine Intelligence (1 paper)2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (1 paper)2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) (1 paper)2021 IEEE/CVF International Conference on Computer Vision (ICCV) (1 paper)

In The Last Decade

Prune Truong

5 papers receiving 184 citations

Peers

Prune Truong
Comparison fields: 5 of 31
  • Computer Vision and Pattern Recognition 156
  • Computer Graphics and Computer-Aided Design 22
  • Geology 7
  • Media Technology 11
  • Aerospace Engineering 31
Replace Hongjia Zhai with:
Hongjia Zhai China
Jian Shi China
Claudia Nieuwenhuis Germany
Toshikazu Wada Japan
Zhaoyang Lyu China
Siddharth Manay United States
Qiaole Dong China
Pierluigi Zama Ramirez Italy
Sungheon Park South Korea
Prune Truong relative to Hongjia Zhai China Hongjia Zhai's profile →
Citations per field
00.5×
Hongjia Zhai · 1×
Citations per year

Countries citing papers authored by Prune Truong

Since Specialization
Citations

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

Fields of papers citing papers by Prune Truong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 10 scholars most cited alongside Prune Truong, 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 Prune Truong Line = papers co-authored together Prune Truong links everyone, so they are left out of the graph.

All Works

6 of 6 papers shown

About Prune Truong

Prune Truong is a scholar working on Computer Vision and Pattern Recognition, Aerospace Engineering, Control and Systems Engineering, Artificial Intelligence and Radiology, Nuclear Medicine and Imaging, having authored 6 papers that have together received 189 indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (3 papers), Robotics and Sensor-Based Localization (2 papers), Advanced Vision and Imaging (2 papers), Advanced Neural Network Applications (2 papers), Human Pose and Action Recognition (2 papers), Multimodal Machine Learning Applications (2 papers), Domain Adaptation and Few-Shot Learning (1 paper) and Hand Gesture Recognition Systems (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (156 citations), Computer Graphics and Computer-Aided Design (22 citations), Geology (7 citations), Media Technology (11 citations) and Aerospace Engineering (31 citations). Prune Truong has collaborated with scholars based in Switzerland, Germany and United States. Frequent co-authors include Luc Van Gool, Martin Danelljan, Marie‐Julie Rakotosaona, Federico Tombari, Fabian Manhardt, Radu Timofte, Fisher Yu, Christos Sakaridis, Siyuan Li and Ajad Chhatkuli. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) and 2021 IEEE/CVF International Conference on Computer Vision (ICCV).

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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