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Some Machine Learning Technologies for Image processing and Beyond

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If you have a question about this talk, please contact Ferdia Sherry .

Machine/deep learning technologies have revolutionised many fields including computer vision and image processing. Their success generally relies on big data. However, for the data scarcity scenarios like in medical imaging, their performance could drop significantly. Moreover, in many cases, they also lack generalisation (e.g. the cross-domain adaptation problem) and explanation (e.g. explainable AI). In this presentation, I will introduce some of our recent work on segmentation and classification targeting those challenges, such as subspace feature representations for few-shot learning, multilevel explainable AI, cross-domain adaptation in point clouds, etc.

This talk is part of the Cambridge Image Analysis Seminars series.

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