How can an artificial intelligence find its bearing in a real environment? How can it understand that an object, or a living thing has moved and make a logic link between an environment at a specific moment and the same environment an instant later? These are all complex questions in a field called computer vision. Segmentation, i.e. breaking down the images in smaller components for tracking; and synchronisation, i.e. the ability to compare different situations in time require advanced mathematical models, which are explained in part in this SPRING Technical Seminar #4, entitled “Synchronisation and Cycle-Consistency in Computer Vision”, by Prof. Federica Arrigoni from University of Trento on 7 July 2020.

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