This work exploits several machine-learning techniques to address the problem of image-quality prediction of synthetic aperture sonar (SAS) imagery. The objective is to predict th...
Abstract. In this paper we introduce a new representation for shapebased object class detection. This representation is based on very sparse and slightly flexible configurations of...
Boosting based detection methods have successfully been used for robust detection of faces and pedestrians. However, a very large amount of labeled examples are required for train...
We propose a method to learn heterogeneous models of object classes for visual recognition. The training images contain a preponderance of clutter and learning is unsupervised. Ou...
3D modelling finds a wide range of applications in industry. However, due to the presence of surface scanning noise, accumulative registration errors, and improper data fusion, re...