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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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Machine Learning for Image Classification. Eligibility You must: We would like you to have: sound knowledge of machine learning, computer vision and image processing strong programming skills. How to apply
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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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of learners as they develop. 3. Develop and evaluate a presentation paradigm to enable non-data science savvy users to get actionable insights into the findings obtained through the measurement framework
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The brain is a complex machine and brain function remains yet to be fully understood. This project works at the intersection of dynamical modelling, statistical signal processing, statistical
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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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the simple equation that more training data = better performance. Learning—in particular, the advanced deep learning methods, like BERT for NLP and ResNet for image processing—often require thousands