Latent Layout Analysis (LLA) is a novel unsupervised learning technique to discover objects in unseen images using a set of un-annotated training images. LLA defines a generative ...
We classify an image by generating a list of salient visual features present in the luminance channel, and matching the resulting variable-length feature list to categoryspecific ...
Many classification tasks benefit from integrating manifold learning and semi-supervised learning. By formulating the learning task in a semi-supervised manner, we propose a novel...
The prediction of protein secondary structure is a classical problem in bioinformatics, and in the past few years several machine learning techniques have been proposed to t. From...
The objectives of the work described in this paper are simply stated: given examples of a particular person and an unlabelled video, we wish to find every instance of that person ...