In this paper, we investigate a simple, mistakedriven learning algorithm for discriminative training of continuous density hidden Markov models (CD-HMMs). Most CD-HMMs for automat...
Many approaches to object recognition are founded on probability theory, and can be broadly characterized as either generative or discriminative according to whether or not the di...
Discriminative approaches for human pose estimation model the functional mapping, or conditional distribution, between image features and 3D pose. Learning such multi-modal models ...
lass Recognition using Images of Abstract Regions Yi Li, Jeff A. Bilmes, and Linda G. Shapiro Department of Computer Science and Engineering Department of Electrical Engineering Un...