Nam Le
Impact in
- Human-Computer Interaction top 2%
- Hand Gesture Recognition Systems
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- Human Pose and Action Recognition
- Video Surveillance and Tracking Methods
Papers in
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- Face recognition and analysis 3
- Video Analysis and Summarization 1
- Video Surveillance and Tracking Methods 1
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- Speech and Audio Processing 4
- Music and Audio Processing 2
- Co-authors
- Jean‐Marc Odobez (6 shared papers)Di Wu (2 shared papers)Ling Shao (1 shared paper)Lionel Pigou (1 shared paper)Pieter-Jan Kindermans (1 shared paper)Joni Dambre (1 shared paper)
- Journals
- Multimedia Tools and Applications (1 paper)IEEE Transactions on Pattern Analysis and Machine Intelligence (1 paper)Infoscience (Ecole Polytechnique Fédérale de Lausanne) (3 papers)
- Partner nations
- SwitzerlandGermanyBelgium
In The Last Decade
Nam Le
6 papers receiving 347 citations
Nam Le's Hit Papers
Peers
Comparison fields: 5 of 55
- Human-Computer Interaction 182
- Computer Vision and Pattern Recognition 236
- Developmental and Educational Psychology 42
- Signal Processing 33
- Artificial Intelligence 89
Countries citing papers authored by Nam Le
This map shows the geographic impact of Nam 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 Nam Le with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nam Le more than expected).
Fields of papers citing papers by Nam Le
This network shows the impact of papers produced by Nam 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 Nam Le. The network helps show where Nam Le may publish in the future.
Co-authors
The 6 scholars most cited alongside Nam Le, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Deep Dynamic Neural Networks for Multimodal Gesture Segmentation and Recognition Hit paper breakdown → | 2016 | 330 |
| 2 | 2016 | 14 | |
| 3 | 2018 | 10 | |
| 4 | 2018 | 3 | |
| 5 | 2016 | 2 | |
| 6 | 2017 | 1 |
About Nam Le
Nam Le is a scholar working on Computer Vision and Pattern Recognition, Signal Processing, Artificial Intelligence, Human-Computer Interaction and Biomedical Engineering, having authored 6 papers that have together received 360 indexed citations. Recurring topics across this work include Speech and Audio Processing (4 papers), Speech Recognition and Synthesis (3 papers), Face recognition and analysis (3 papers), Music and Audio Processing (2 papers), Video Analysis and Summarization (1 paper), Hand Gesture Recognition Systems (1 paper), Video Surveillance and Tracking Methods (1 paper) and Gait Recognition and Analysis (1 paper). The work is most often cited by research in Human-Computer Interaction (182 citations), Computer Vision and Pattern Recognition (236 citations), Developmental and Educational Psychology (42 citations), Signal Processing (33 citations) and Artificial Intelligence (89 citations). Nam Le has collaborated with scholars based in Switzerland, Germany and Belgium. Frequent co-authors include Jean‐Marc Odobez, Di Wu, Ling Shao, Lionel Pigou, Pieter-Jan Kindermans and Joni Dambre. Their work appears in journals such as Multimedia Tools and Applications, IEEE Transactions on Pattern Analysis and Machine Intelligence and Infoscience (Ecole Polytechnique Fédérale de Lausanne).
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.