Unsupervised learning algorithms aim to discover the structure hidden in the data, and to learn representations that are more suitable as input to a supervised machine than the ra...
Reasoning about spatial data is a key task in many applications, including geographic information systems, meteorological and fluid flow analysis, computer-aided design, and prote...
Bayesian parameter estimation can be used to generate statistically optimal solutions to the problem of cue integration. However, the complexity and dimensionality of these solutio...
The bounding box representation employed by many popular object detection models [3, 6] implicitly assumes all pixels inside the box belong to the object. This assumption makes th...
Image composition (or mosaicing) has attracted a growing attention in recent years as one of the main elements in video analysis and representation. In this paper we deal with the...