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Lecture Notes in Computer Science
In this paper, we propose a new partially supervised multiclass image segmentation algorithm. We focus on the multi-class, singlelabel setup, where each image is assigned one of multiple classes. We formulate the problem of image segmentation as a multi-instance task on a given set of overlapping candidate segments. Using these candidate segments, we solve the multi-instance, multi-class problem using multi-instance kernels with an SVM. This computationally advantageous approach, which requiresdoi:10.1007/978-3-642-28258-4_12 fatcat:a5knctennjbahcnqxbld7e33s4