Clustering is the unsupervised classification of patterns (observations, data items, or feature
vectors) into groups (clusters). The clustering problem has been addressed in many contexts …

Texture analysis is used in a very broad range of fields and applications, from texture
classification (eg, for remote sensing) to segmentation (eg, in biomedical imaging), passing …

We develop a framework for learning generic, expressive image priors that capture the
statistics of natural scenes and can be used for a variety of machine vision tasks. The …

This paper presents the current status of a new initiative aimed at develo** a versatile
framework and image database for empirical evaluation of texture analysis algorithms. The …

While remote sensing has made enormous progress over recent years and a variety of
sensors now deliver medium and high resolution data on an operational basis, a vast …

We address the problem of blind motion deblurring from a single image, caused by a few
moving objects. In such situations only part of the image may be blurred, and the scene …

To detect landslides by object-based image analysis using criteria based on shape, color,
texture, and, in particular, contextual information and process knowledge, candidate …

This paper proposes a novel colorization technique that propagates color over regions
exhibiting pattern-continuity as well as intensity-continuity. The proposed method works …

With the increasing popularity of Internet commerce, a wealth of information about the
customers can now be readily acquired on-line. An important example is the customers' …

Power quality issues are required to be addressed properly in forthcoming era of smart
meters, smart grids and increase in renewable energy integration. In this paper, Deep Auto …