The National Cancer Institute has collected a large database of digitized 35mm slides of the uterine cervix, the idea being to build a system enabling to study the evolution of le...
Given an image, we propose a hierarchical generative
model that classifies the overall scene, recognizes and segments
each object component, as well as annotates the image
with ...
Accurate image segmentation is important for many image, video and computer vision applications. Over the last few decades, many image segmentation methods have been proposed. How...
We present a quantitative evaluation of SE-MinCut, a novel segmentation algorithm based on spectral embedding and minimum cut. We use human segmentations from the Berkeley Segment...
Multiple Instance Learning (MIL) provides a framework for training a discriminative classifier from data with ambiguous labels. This framework is well suited for the task of learni...
Carolina Galleguillos, Boris Babenko, Andrew Rabin...