- Dr Mohammad Mahfujur Rahman
- Research Fellow
Science and Engineering Faculty,
School of Electrical Engineering & Robotics
- +61 416 453 032
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Computer Vision, Machine Learning, Deep Learning, Domain Adaptation, Domain Generalization, Pattern Recognition
Dr Mohammad Mahfujur Rahman is a Research Fellow in Signal Processing, Artificial Intelligence and Vision Technologies (SAIVT) research group within the School of Electrical Engineering and Robotics of the Science and Engineering Faculty at Queensland University of Technology (QUT). He received his PhD degree in the fields of computer vision and deep learning from QUT, Australia. His PhD research addressed a critical problem in deep neural networks and computer vision with dataset bias between the source and target environments. During his PhD, he introduced several domain adaptation and generalisation approaches based on deep neural networks to improve poor performance due to domain shift or domain bias.
Dr Mahfujur actively researches in the fields of computer vision and machine learning including transfer learning, domain adaptation, domain generalisation, object detection and classification. He aims to utilise deep transfer learning and domain adaptation techniques to enable visual learning.
- Rahman M, Fookes C, Baktashmotlagh M, Sridharan S, (2020) Correlation-aware adversarial domain adaptation and generalization, Pattern Recognition p1-13
- Rahman M, Fookes C, Baktashmotlagh M, Sridharan S, (2019) Multi-Component Image Translation for Deep Domain Generalization, Proceedings of the 2019 IEEE Winter Conference on Applications of Computer Vision (WACV 2019) p579-588
- Rahman M, Fookes C, Baktashmotlagh M, Sridharan S, (2020) On Minimum Discrepancy Estimation for Deep Domain Adaptation, Domain Adaptation for Visual Understanding p81-94
For more publications by this staff member, visit QUT ePrints, the University's research repository.