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Lecture Notes in Computer Science
Unsupervised image clustering is a challenging and often ill-posed problem. Existing image descriptors fail to capture the clustering criterion well, and more importantly, the criterion itself may depend on (unknown) user preferences. Semi-supervised approaches such as distance metric learning and constrained clustering thus leverage user-provided annotations indicating which pairs of images belong to the same cluster (must-link) and which ones do not (cannot-link). These approaches requiredoi:10.1007/978-3-319-10599-4_22 fatcat:sm6a7xht2zewfn7tv3tgll4m4i