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fall detection would be from video as it does not require wearing a device and remembering to charge it and so on. But computer vision-based falls detection in the elderly can be problematic due
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revolutionized the field of artificial intelligence, leading to remarkable advancements across many applications ranging from image classification to natural language processing. Despite these successes
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involves sending mean, vulgar, or threatening messages or images, posting sensitive, private information and/or lies about another person to make that person look bad, and intentionally excluding someone
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(e.g., C++, Unity, Python) a background or interest in human-computer interaction, gender studies, and/or construction familiarity with qualitative and quantitative research methods. How to apply We
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. The latest advanced techniques in machine learning and computer vision for image content analysis will be applied to generate data for dynamic species distribution models. This data will in turn be used
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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
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. This would provide thousands of diverse example images with corresponding body part locations. These data would be used to train a deep learning model 5, 7 . The model’s high-quality body part predictions may
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This project will seek to further the research into and development of machine learning techniques that may be used to triage, classify, and otherwise process material of a distressing nature (such
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include: 1. Identify a novel co-design methodology along with the structural templates that could be used to drive the further design process of collocated teamwork analytics with critical educational