Kernel machines have been shown as the state-of-the-art learning techniques for classification. In this paper, we propose a novel general framework of learning the Unified Kernel ...
We present a set of methods to enable a cross-domain reuse of problem solutions via analysis patterns. First, problem-context descriptions and problemcontext models as well as sol...
This paper describes a complete approach to detect, localize and describe network patterns. Such texture is automatically detected with Gaussian derivative kernels and Fisher line...
Costantino Grana, Giovanni Pellacani, Rita Cucchia...
A large family of shape comparison methods is based on a medial axis transform combined with an encoding of the skeleton by a graph. Despite many qualities this encoding of shapes ...