The use of higher order autocorrelations as features for pattern classification has been usually restricted to second or third orders due to high computational costs. Since the au...
Manifold Pursuit (MP) extends Principal Component Analysis to be invariant to a desired group of image-plane transformations of an ensemble of un-aligned images. We derive a simpl...
Abstract. This paper proposes a statistical model of functional landmarks delimiting low level visual areas which are highly variable across individuals. Low level visual areas are...
Isabelle Corouge, Michel Dojat, Christian Barillot
Training principles for unsupervised learning are often derived from motivations that appear to be independent of supervised learning. In this paper we present a simple unificatio...
This paper presents a Local Learning Projection (LLP) approach for linear dimensionality reduction. We first point out that the well known Principal Component Analysis (PCA) essen...