To reduce the high dimensionality required for training of feature vectors in speaker identification, we propose an efficient GMM based on local PCA with Fuzzy clustering. The prop...
Reducing the dimension of local descriptors in images is useful to perform pixels comparison faster. We show here that, for enhancing and optimising the computation of the NL-mean...
Linear Discriminant Analysis (LDA) is a well-known scheme for feature extraction and dimension reduction. It has been used widely in many applications involving high-dimensional d...
Abstract: This paper discusses three rectilinear (that is, axis-parallel) covering problems in d dimensions and their variants. The first problem is the Rectilinear Line Cover whe...
Vladimir Estivill-Castro, Apichat Heednacram, Fran...
Roughly speaking, adequatness is the property of a theorem proving method to solve simpler problems faster than more difficult ones. Automated inferencing methods are often not ad...