CAS/CNS Technical Reports
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Contrast-sensitive perceptual grouping and object-based attention in the laminar circuits of primary visual cortex
(Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1999-03)Recent neurophysiological studies have shown that primary visual cortex, or Vl, does more than passively process image features using the feedforward filters suggested by Hubel and Wiesel. It also uses horizontal interactions ... -
A laminar cortical model of stereopsis and 3D surface perception: Closure and da Vinci stereopsis
(Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 2004-09)A laminar cortical model of stereopsis and 3D surface perception is developed and simulated. The model describes how monocular and binocular oriented filtering interact with later stages of 3D boundary formation and surface ... -
PointMap: A real-time memory-based learning system with on-line and post-training pruning
(Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 2002-12)A memory-based learning system called PointMap is a simple and computationally efficient extension of Condensed Nearest Neighbor that allows the user to limit the number of exemplars stored during incremental learning. ... -
The Role of Edges and Line-Ends in Illusory Contour Formation
(Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1994-04)Illusory contours can be induced along directions approximately collinear to edges or approximately perpendicular to the ends of lines. Using a rating scale procedure we explored the relation between the two types of ... -
Fuzzy ART
(Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1993-12-15)Adaptive Resonance Theory (ART) models are real-time neural networks for category learning, pattern recognition, and prediction. Unsupervised fuzzy ART and supervised fuzzy ARTMAP synthesize fuzzy logic and ART networks ... -
Spatial Pattern Learning, Catastophic Forgetting and Optimal Rules of Synaptic Transmission
(Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1995-03)It is a neural network truth universally acknowledged, that the signal transmitted to a target node must be equal to the product of the path signal times a weight. Analysis of catastrophic forgetting by distributed codes ... -
Unsupervised Neural Network for the Control of a Mobile Robot
(Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1993-10)This article introduces an unsupervised neural architecture for the control of a mobile robot. The system allows incremental learning of the plant during robot operation, with robust performance despite unexpected changes ... -
A Network for Learning Kinematics with Application to Human Reaching Models
(Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1993-10)A model for self-organization of the coordinate transformations required for spatial reaching is presented. During a motor babbling phase, a mapping from spatial coordinate directions to joint motion directions is learned. ... -
Rule Extraction, Fuzzy ARTMAP, and Medical Databases
(Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1993-01)This paper shows how knowledge, in the form of fuzzy rules, can be derived from a self-organizing supervised learning neural network called fuzzy ARTMAP. Rule extraction proceeds in two stages: pruning removes those ... -
ART-EMAP: A Neural Network Architecture for Learning and Prediction by Evidence Accumulation
(Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1993-01)This paper introduces ART-EMAP, a neural architecture that uses spatial and temporal evidence accumulation to extend the capabilities of fuzzy ARTMAP. ART-EMAP combines supervised and unsupervised learning and a medium-term ...