We present a method to learn object class models from unlabeled and unsegmented cluttered scenes for the purpose of visual object recognition. We focus on a particular type of mode...
Abstract— Separate processing of local luminance and contrast in biological visual systems has been argued to be due to the independence of these two properties in natural image ...
We present an algorithm, Nomen, for learning generalized names in text. Examples of these are names of diseases and infectious agents, such as bacteria and viruses. These names ex...
—Reading text from photographs is a challenging problem that has received a signicant amount of attention. Two key components of most systems are (i) text detection from images a...
Adam Coates, Blake Carpenter, Carl Case, Sanjeev S...
In this paper we present a framework for using multi-layer perceptron (MLP) networks in nonlinear generative models trained by variational Bayesian learning. The nonlinearity is h...