D
Duy Lê Data-verified
Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.
Researcher
faculty
5 h-index
20 pubs
109 cited
Research Areas
Links
Biography and Research Information
OverviewAI-generated summary
Duy Lê's research investigates the application of advanced neural network models, particularly deep learning and diffusion models, for complex data analysis and detection tasks. His work includes developing efficient attentive pillar networks for real-time 3D pedestrian detection and exploring diffusion models for robust multi-sensor fusion in 3D object detection and Bird's Eye View (BEV) segmentation. Lê has also focused on creating deep convolutional neural networks, such as AFFnet, for the detection of atypical femur fractures from anterior-posterior radiographs. His research extends to dataset creation for multi-person pose estimation and tracking, as demonstrated by the JRDB-Pose and JRDB-PanoTrack datasets. Collaborations include shared publications with researchers such as Michael T. Kidd and Tran-Dac-Thinh Phan.
Metrics
- h-index: 5
- Publications: 20
- Citations: 109
Selected Publications
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BroilerTrack: Automatic multi-camera multi-broiler tracking (2025)
Collaboration Network
Top Collaborators
Hamid Rezatofighi
Monash University (AU)
6 shared publications
- Accurate and Real-Time 3D Pedestrian Detection Using an Efficient Attentive Pillar Network
- JRDB-Pose: A Large-Scale Dataset for Multi-Person Pose Estimation and Tracking
- Diffusion Model for Robust Multi-sensor Fusion in 3D Object Detection and BEV Segmentation
- JRDB-PanoTrack: An Open-World Panoptic Segmentation and Tracking Robotic Dataset in Crowded Human Environments
- Improving Visual Perception of a Social Robot for Controlled and In-the-wild Human-robot Interaction
Showing 5 of 6 shared publications
Jianfei Cai
Monash University (AU)
6 shared publications
- Accurate and Real-Time 3D Pedestrian Detection Using an Efficient Attentive Pillar Network
- JRDB-Pose: A Large-Scale Dataset for Multi-Person Pose Estimation and Tracking
- Diffusion Model for Robust Multi-sensor Fusion in 3D Object Detection and BEV Segmentation
- AFFnet - a deep convolutional neural network for the detection of atypical femur fractures from anteriorposterior radiographs
- JRDB-PanoTrack: An Open-World Panoptic Segmentation and Tracking Robotic Dataset in Crowded Human Environments
Showing 5 of 6 shared publications
Linh Nguyen
Federation University (AU)
3 shared publications
- An Efficient Multi-Vehicle Routing Strategy for Goods Delivery Services
- A Design of Haptic Hand Exoskeleton for Virtual Reality Applications
- Simple linear iterative clustering based low-cost pseudo-LiDAR for 3D object detection in autonomous driving
Hengcan Shi
Hunan University (CN)
3 shared publications
- Accurate and Real-Time 3D Pedestrian Detection Using an Efficient Attentive Pillar Network
- Diffusion Model for Robust Multi-sensor Fusion in 3D Object Detection and BEV Segmentation
- JRDB-PanoTrack: An Open-World Panoptic Segmentation and Tracking Robotic Dataset in Crowded Human Environments
Edward Vendrow
Stanford University (US)
2 shared publications
- JRDB-Pose: A Large-Scale Dataset for Multi-Person Pose Estimation and Tracking
- JRDB-Pose: A Large-scale Dataset for Multi-Person Pose Estimation and Tracking
Hanh H. Nguyen
Monash Health (AU)
2 shared publications
- AFFnet - a deep convolutional neural network for the detection of atypical femur fractures from anteriorposterior radiographs
- Affnet - a Deep Convolutional Neural Network for the Detection of Atypical Femur Fractures from Anteriorposterior Radiographs
Catherine Shore‐Lorenti
Monash University (AU)
2 shared publications
- AFFnet - a deep convolutional neural network for the detection of atypical femur fractures from anteriorposterior radiographs
- Affnet - a Deep Convolutional Neural Network for the Detection of Atypical Femur Fractures from Anteriorposterior Radiographs
Colin Chen
Monash University (AU)
2 shared publications
- AFFnet - a deep convolutional neural network for the detection of atypical femur fractures from anteriorposterior radiographs
- Affnet - a Deep Convolutional Neural Network for the Detection of Atypical Femur Fractures from Anteriorposterior Radiographs
Jörg Schilcher
Linköping University (SE)
2 shared publications
- AFFnet - a deep convolutional neural network for the detection of atypical femur fractures from anteriorposterior radiographs
- Affnet - a Deep Convolutional Neural Network for the Detection of Atypical Femur Fractures from Anteriorposterior Radiographs
Anders Eklund
Linköping University (SE)
2 shared publications
- AFFnet - a deep convolutional neural network for the detection of atypical femur fractures from anteriorposterior radiographs
- Affnet - a Deep Convolutional Neural Network for the Detection of Atypical Femur Fractures from Anteriorposterior Radiographs
Roger Zebaze
Monash University (AU)
2 shared publications
- AFFnet - a deep convolutional neural network for the detection of atypical femur fractures from anteriorposterior radiographs
- Affnet - a Deep Convolutional Neural Network for the Detection of Atypical Femur Fractures from Anteriorposterior Radiographs
Frances Milat
Monash Health (AU)
2 shared publications
- AFFnet - a deep convolutional neural network for the detection of atypical femur fractures from anteriorposterior radiographs
- Affnet - a Deep Convolutional Neural Network for the Detection of Atypical Femur Fractures from Anteriorposterior Radiographs
Shoshana Sztal‐Mazer
Monash University (AU)
2 shared publications
- AFFnet - a deep convolutional neural network for the detection of atypical femur fractures from anteriorposterior radiographs
- Affnet - a Deep Convolutional Neural Network for the Detection of Atypical Femur Fractures from Anteriorposterior Radiographs
Christian M. Girgis
Westmead Hospital (AU)
2 shared publications
- AFFnet - a deep convolutional neural network for the detection of atypical femur fractures from anteriorposterior radiographs
- Affnet - a Deep Convolutional Neural Network for the Detection of Atypical Femur Fractures from Anteriorposterior Radiographs
Roderick Clifton‐Bligh
Royal North Shore Hospital (AU)
2 shared publications
- AFFnet - a deep convolutional neural network for the detection of atypical femur fractures from anteriorposterior radiographs
- Affnet - a Deep Convolutional Neural Network for the Detection of Atypical Femur Fractures from Anteriorposterior Radiographs
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