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intelligence, Machine learning, and Computer vision for subsurface characterisation This project aims to develop computer vision applications for geological characterisation using state-of-the-art AI/ML methods
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self-motivated PhD candidate with excellent academic record, expertise in Python and machine learning. Application process This project has identified a preferred candidate and is no longer available
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, Machine Learning, and Software Engineering. The HPIS group consists of leading computer science experts and works closely with different industries, e.g., Australian Defence, Governments, Software
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on leveraging advanced computer vision (CV) and deep learning (DL) techniques to develop a state-of-the-art computer-aided detection and diagnosis (CAD) system for early-stage Alzheimer's disease (AD) detection
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machine learning to identify meteorites in aerial imagery, with great success, and recovered multiple meteorites using a UAV. This project will build on this success, by extending the drone approach to new
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AI models including computer vision will be complemented by some experiment conduct experiences. The applicant must be eligible to enrol in PhD program at Curtin University, and physically present in
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team of collaborators and stakeholders with expertise in biomechanics, spatial and speech sciences, computer vision, machine learning, and clinical experience in the diagnosis/management of Speech Sound
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video as it does not require wearing a device and remebering to charge it and so on. But computer vision-based falls detection in the elderly can be problematic due to false privacy concerns, cost, and
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courses Eligibility criteria Cybersecurity Knowledge, Coding, Network and Communication Protocols, Familiarity with Autonomous Vehicle Systems, Data Analysis and Machine Learning, Continuous Learning
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with your current location and preferences. Our project aims to create an intelligent recommender system that seamlessly integrates geospatial data, leveraging advanced algorithms and machine learning