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Explore an open-source project dedicated to combating COVID-19 through machine learning in this EuroPython 2020 conference talk. Dive into Corona-Net, a three-part initiative focusing on classification, binary segmentation, and multi-class segmentation of COVID-19 using chest CT scans. Learn about the implementation of EfficientNet for diagnosis and the refinement of U-Net architecture for symptom segmentation. Discover how this project aims to develop a reliable, visually-semantically balanced method for automatic COVID-19 diagnosis while inviting collaboration in the global fight against the pandemic. Gain insights into the project's background, problem statement, model architecture, classification techniques, fully convolutional networks, and future development plans.
