Alberto Taboada-Crispí

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In this paper, we propose a two-phase approach to nuclei segmentation/classification in Pap smear test images. The first phase, the segmentation phase, includes a morphological algorithm (watershed) and a hierarchical merging algorithm (waterfall). In the merging step, waterfall uses spectral and shape information as well as the class information. In the(More)
The development of Multiple Kernel Techniques has become of particular interest for machine learning researchers in Computer Vision topics like image processing, object classification, and object state recognition. Sparsity-inducing norms along with non-sparse formulations promote different degrees of sparsity at the kernel coefficient level, at the same(More)
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