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Fast Learning by Bounding Likelihoods in Sigmoid Type Belief Networks
(1996-02-09)
Sigmoid type belief networks, a class of probabilistic neural networks, provide a natural framework for compactly representing probabilistic information in a variety of unsupervised and supervised learning problems. ...
Model-Based Matching by Linear Combinations of Prototypes
(1996-12-01)
We describe a method for modeling object classes (such as faces) using 2D example images and an algorithm for matching a model to a novel image. The object class models are "learned'' from example images that we call ...
Model-Based Matching of Line Drawings by Linear Combinations of Prototypes
(1996-01-18)
We describe a technique for finding pixelwise correspondences between two images by using models of objects of the same class to guide the search. The object models are 'learned' from example images (also called ...
Neural Networks
(1996-03-13)
We present an overview of current research on artificial neural networks, emphasizing a statistical perspective. We view neural networks as parameterized graphs that make probabilistic assumptions about data, and view ...
Model Selection in Summary Evaluation
(2002-12-01)
A difficulty in the design of automated text summarization algorithms is in the objective evaluation. Viewing summarization as a tradeoff between length and information content, we introduce a technique based on ...
Role of Low-level Mechanisms in Brightness Perception
(2001-08-01)
Brightness judgments are a key part of the primate brain's visual analysis of the environment. There is general consensus that the perceived brightness of an image region is based not only on its actual luminance, but also ...
Multiclass Classification of SRBCTs
(2001-08-25)
A novel approach to multiclass tumor classification using Artificial Neural Networks (ANNs) was introduced in a recent paper cite{Khan2001}. The method successfully classified and diagnosed small, round blue cell tumors ...
Biologically Plausible Neural Circuits for Realization of Maximum Operations
(2001-09-01)
Object recognition in the visual cortex is based on a hierarchical architecture, in which specialized brain regions along the ventral pathway extract object features of increasing levels of complexity, accompanied by greater ...
Perceptually-based Comparison of Image Similarity Metrics
(2001-07-01)
The image comparison operation ??sessing how well one image matches another ??rms a critical component of many image analysis systems and models of human visual processing. Two norms used commonly for this purpose are L1 ...
Contextual Priming for Object Detection
(2001-09-01)
There is general consensus that context can be a rich source of information about an object's identity, location and scale. In fact, the structure of many real-world scenes is governed by strong configurational rules akin ...