Classification is one of the most fundamental problems in machine learning, which aims to separate the data from different classes as far away as possible. A common way to get a g...
Bin Zhang, Fei Wang, Ta-Hsin Li, Wen Jun Yin, Jin ...
Holistic representations of natural scenes are an effective and powerful source of information for semantic classification and analysis of arbitrary images. Recently, the frequenc...
Sebastiano Battiato, Giovanni Maria Farinella, Gio...
The aim of this paper is to propose tools for statistical analysis of shape families using morphological operators. Given a series of shape families (or shape categories), the appr...
This research reports an ethnographic study of issues surrounding digital technologies owned and used by homeless people in Los Angeles County. We identify two themes—survival a...
: A new supervised learning procedure for training RBF networks is proposed. It uses a pair of parallel running Kalman filters to sequentially update both the output weights and th...