M
Minh Quan Tran Data-verified
Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.
Postdoc
postdoc
11 h-index
69 pubs
1,129 cited
Research Areas
Links
Biography and Research Information
OverviewAI-generated summary
Minh Quan Tran's research focuses on the application of advanced computational techniques, particularly deep learning and transformer models, to diverse problems. His work has involved developing algorithms for automatic sleep staging, as demonstrated by "XSleepNet: Multi-View Sequential Model for Automatic Sleep Staging" and "L-SeqSleepNet: Whole-cycle Long Sequence Modeling for Automatic Sleep Staging." Tran has also explored applications in autonomous driving with "Deep Federated Learning for Autonomous Driving" and in medical image analysis and question answering through "Multiple Meta-model Quantifying for Medical Visual Question Answering." His expertise extends to aerial image segmentation with "AerialFormer: Multi-Resolution Transformer for Aerial Image Segmentation" and emotion recognition using audio-visual transformers. He has also contributed to research on deformable image registration and the development of open-source toolkits for facial expression analysis like "LibreFace."
Metrics
- h-index: 11
- Publications: 69
- Citations: 1,129
Selected Publications
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DualFit: A Two-Stage Virtual Try-On via Warping and Synthesis (2025)
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Land8Fire: A Complete Study on Wildfire Segmentation Through Comprehensive Review, Human-Annotated Multispectral Dataset, and Extensive Benchmarking (2025)
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Miga: Multi-Chicken Gait Assessment (2025)
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A2VIS: Amodal-Aware Approach to Video Instance Segmentation (2025)
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S3Former: A Deep Learning Approach to High Resolution Solar PV Profiling (2025)
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AerialFormer: Multi-Resolution Transformer for Aerial Image Segmentation (2024)
Collaboration Network
Top Collaborators
Tuong Do
4 shared publications
- Deep Federated Learning for Autonomous Driving
- Multiple Meta-model Quantifying for Medical Visual Question Answering
- Light-Weight Deformable Registration Using Adversarial Learning With Distilling Knowledge
- Multiple Meta-model Quantifying for Medical Visual Question Answering
Erman Tjiputra
4 shared publications
- Deep Federated Learning for Autonomous Driving
- Multiple Meta-model Quantifying for Medical Visual Question Answering
- Light-Weight Deformable Registration Using Adversarial Learning With Distilling Knowledge
- Multiple Meta-model Quantifying for Medical Visual Question Answering
Quang D. Tran
4 shared publications
- Deep Federated Learning for Autonomous Driving
- Multiple Meta-model Quantifying for Medical Visual Question Answering
- Light-Weight Deformable Registration Using Adversarial Learning With Distilling Knowledge
- Multiple Meta-model Quantifying for Medical Visual Question Answering
Anh Nguyen
University of Liverpool (GB)
4 shared publications
- Deep Federated Learning for Autonomous Driving
- Multiple Meta-model Quantifying for Medical Visual Question Answering
- Light-Weight Deformable Registration Using Adversarial Learning With Distilling Knowledge
- Multiple Meta-model Quantifying for Medical Visual Question Answering
Binh X. Nguyen
3 shared publications
- Deep Federated Learning for Autonomous Driving
- Multiple Meta-model Quantifying for Medical Visual Question Answering
- Multiple Meta-model Quantifying for Medical Visual Question Answering
Dmitriy Bekker
Johns Hopkins University Applied Physics Laboratory (US)
3 shared publications
- Didymos Reconnaissance and Asteroid Camera for OpNav (DRACO): design, fabrication, test, and operation
- The Design and Verification of the DART Single Board Computer FPGA
- Guiding DART to Impact — the FPGA SoC Design of the DRACO Image Processing Pipeline
Ronald D. Smith
Johns Hopkins University Applied Physics Laboratory (US)
3 shared publications
- Didymos Reconnaissance and Asteroid Camera for OpNav (DRACO): design, fabrication, test, and operation
- The Design and Verification of the DART Single Board Computer FPGA
- Guiding DART to Impact — the FPGA SoC Design of the DRACO Image Processing Pipeline
Ngan Le
University of Arkansas at Fayetteville (US)
3 shared publications
- CarcassFormer: an end-to-end transformer-based framework for simultaneous localization, segmentation and classification of poultry carcass defect
- S3Former: A Deep Learning Approach to High Resolution Solar PV Profiling
- CarcassFormer: An End-to-end Transformer-based Framework for Simultaneous Localization, Segmentation and Classification of Poultry Carcass Defect
Steven Zhan
Johns Hopkins University Applied Physics Laboratory (US)
2 shared publications
- The Design and Verification of the DART Single Board Computer FPGA
- Titan Bound: The FPGA SoC Design of the Navigation Coprocessor Controller
Jeffrey Boye
Johns Hopkins University Applied Physics Laboratory (US)
2 shared publications
- The Design and Verification of the DART Single Board Computer FPGA
- Titan Bound: The FPGA SoC Design of the Navigation Coprocessor Controller
Matthew Gile
Johns Hopkins University Applied Physics Laboratory (US)
2 shared publications
- The Design and Verification of the DART Single Board Computer FPGA
- Titan Bound: The FPGA SoC Design of the Navigation Coprocessor Controller
Christopher J. Monaghan
Johns Hopkins University Applied Physics Laboratory (US)
2 shared publications
- The Design and Verification of the DART Single Board Computer FPGA
- Titan Bound: The FPGA SoC Design of the Navigation Coprocessor Controller
Sang Truong
University of Arkansas at Fayetteville (US)
2 shared publications
- CarcassFormer: an end-to-end transformer-based framework for simultaneous localization, segmentation and classification of poultry carcass defect
- CarcassFormer: An End-to-end Transformer-based Framework for Simultaneous Localization, Segmentation and Classification of Poultry Carcass Defect
Arthur Fernandes
2 shared publications
- CarcassFormer: an end-to-end transformer-based framework for simultaneous localization, segmentation and classification of poultry carcass defect
- CarcassFormer: An End-to-end Transformer-based Framework for Simultaneous Localization, Segmentation and Classification of Poultry Carcass Defect
Michael T. Kidd
2 shared publications
- CarcassFormer: an end-to-end transformer-based framework for simultaneous localization, segmentation and classification of poultry carcass defect
- CarcassFormer: An End-to-end Transformer-based Framework for Simultaneous Localization, Segmentation and Classification of Poultry Carcass Defect
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