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The ongoing liberalization of the energy market makes energy providers increasingly look at premium services -- like personalized energy consulting -- as preferred methods to bind existing customers and attract new ones. Providing such services, however, requires knowledge of specific properties of the customer's household -- like its size and the number of(More)
Interest in analyzing electricity consumption data of private households has grown steadily in the last years. Several authors have for instance focused on identifying groups of households with similar consumption patterns or on providing feedback to consumers in order to motivate them to reduce their energy consumption. In this paper, we propose to use(More)
In this paper, a Sparse Representation based Classification (SRC) approach is employed for mine hunting using Synthetic Aperture Sonar (SAS) images. Given a training database with enough samples, SRC exploits the properties of sparse signals and expresses a sample of unknown class as a sparse linear combination of the training samples. The class of the(More)
In the context of automatic detection and classification for mine hunting applications, a high quality segmentation of sonar images is mandatory. Assuming a Markov Random Fields representation of the images, we propose a min-cut/max-flow segmentation algorithm. We introduce an original initialization of the graph cut algorithm based on the segmentation(More)
—Utilities increasingly leverage knowledge on their customer's household characteristics in their energy efficiency programs. Examples of such characteristics include the number of persons per household, their employment status, or the type of dwelling they live in. This information allows utilities to personalize energy efficiency campaigns, which(More)
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