We present a novel framework for multi-label learning that explicitly addresses the challenge arising from the large number of classes and a small size of training data. The key a...
Natural images and photographs sometimes may contain stains or undesired objects covering significant portions of the images. Inpainting is a method to fill in such portions using ...
Multi-label learning deals with data associated with multiple labels simultaneously. Previous work on multi-label learning assumes that for each instance, the "full" lab...
Abstract. In engineering protein variants by constructing and screening combinatorial libraries of chimeric proteins, two complementary and competing goals are desired: the new pro...
In this work, we propose the use of a modified version of the correlation coefficient as a performance criterion for the image alignment problem. The proposed modification has the ...