{Learning} How to {Cluster} in {Image} Analysis


In this talk, I will give an overview of my main research interests around subspace clustering, active learning, and the applications to images (image clustering) and on images (image segmentation). For the first half of the talk, I will discuss the use of subspace clustering and active learning for image clustering. Subspace clustering is suited for modelling a group of high-dimensional data that come from a union of various lower-dimensional subspace structures. Active learning addresses the question of how to improve the model performance most effectively and efficiently by querying the least amount of labelling information. For the second half of the talk, I will branch from the problem of clustering images to clustering on images. This concerns the area of image segmentation, which is the subject of my current research.

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