Learning-enhanced relevance feedback is one of the most promising and active research directions in recent year's content-based image retrieval. However, the existing approac...
Abstract. We introduce a novel approach for separating and segmenting individual facades from streetside images. Our algorithm incorporates prior knowledge about arbitrarily shaped...
Relevance feedback has been proposed as an important technique to boost the retrieval performance in content-based image retrieval (CBIR). However, since there exists a semantic g...
Statistical learning methods are emerging as a valuable tool for decoding information from neural imaging data. The noisy signal and the limited number of training patterns that ar...
In this paper we present a new super resolution Bayesian method for pansharpening of multispectral images which: a) incorporates prior knowledge on the expected characteristics of...
Rafael Molina, Miguel Vega, Javier Mateos, Aggelos...