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This project aims to develop robust algorithms capable of identifying and analyzing fingertips extracted from both static images and video footage. Machine learning techniques, particularly computer
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“Revealing Order in Organic Semiconductors with Cryo-Electron Microscopy.” The successful candidate will apply and develop advanced cryo-electron diffraction and imaging methods to uncover structure–property
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the area of end-to-end modular autonomous driving using computer vison and deep learning methods. This includes developing an efficient and interpretable image processing, vision-based perception and
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research in areas such as machine learning, clinical decision-support, medical imaging, and data-driven health services innovation. The position is expected to develop an independent research profile
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methods, and, more broadly, in the physics of imaging and materials science. The position will work in close collaboration with Professor Jian-Min Zuo, Director of the Monash Centre for Electron Microscopy
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, and, more broadly, in the physics of imaging and materials science. The position will utilise instruments in the Monash Centre for Electron Microscopy which has a powerful suite of instrumentation
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Challenges in AI for Pathology Optimal Design of Control Charts for Enhanced Statistical Process Control Digital Twin and AI for Real-Time Environmental Simulation Mobile AI for Food Image Recognition Using
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from standard camera imagery. Such spatial computing applications represent the most significant paradigm shift in human-computer interaction (HCI) since the introduction of graphical user interfaces
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development lifecycle greatly improves its quality and productivity. Here calls for a systematic development lifecycle for the DL systems. Due to the fundamentally different programming paradigm and logic
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the opportunity to address the healthcare inequality for the rural and remote. As one of the most important medical imaging modalities, MRI has long been an advantage only for people living in urban cities due