In this paper, a region-based spatio-temporal Markov random field (STMRF) model is proposed to segment moving objects semantically. The STMRF model combines segmentation results o...
In this paper we propose the "Classification-Based Learning of Subsumption Relations for the Alignment of Ontologies" (CSR) method. Given a pair of concepts from two onto...
Vassilis Spiliopoulos, Alexandros G. Valarakos, Ge...
- Rate-distortion theory is applied to the problem of joint compression and classification. A Lagrangian distortion measure is used to consider both the squared Euclidean error in ...
Abstract. We evaluated methods of protein classification that use kernels built from BLAST output parameters. Protein sequences were represented as vectors of parameters (e.g. simi...
The assignment of alternatives (observations/objects) into predefined homogenous groups is a problem of major practical and research interest. This type of problem is referred to ...