Articles listed below focus on analysis and applications of neural network systems originally developed by CELEST faculty, including ART, ARTMAP, and BCS/FCS.
| Categories |
Topics:
Biological Learning,
Models:
Modified ART, |
| Author(s) |
Grossberg, S. |
Mingolla, E. |
Fazl, A. |
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| Abstract |
How does the brain learn to recognize an object from multiple viewpoints while scanning a scene with eye movements? How does the brain avoid the problem of erroneously classifying parts of different objects together? How are ... |
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Topics:
Other,
Applications:
Other,
Models:
Other, |
| Author(s) |
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| Abstract |
Frequently, a computer program requires input parameters to define a specific application prior to running it. For codes
that require few input parameters, the usual method to define these parameters is to store them in a ... |
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| Categories |
Topics:
Machine Learning,
Models:
ARTMAP, |
| Author(s) |
Carpenter, G.A. |
Gaddam, C.S. |
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| Abstract |
Memories in Adaptive Resonance Theory (ART) networks are based on matched patterns that focus attention on those portions of bottom-up inputs that match active top-down expectations. While this learning strategy has proved ... |
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| Categories |
Topics:
Machine Learning,
Models:
ARTMAP, |
| Author(s) |
Amis, G.P. |
Carpenter, G.A. |
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| Abstract |
Computational models of learning typically train on labeled input patterns (supervised learning), unlabeled input patterns (unsupervised learning), or a combination of the two (semi-supervised learning). In each case input ... |
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| Categories |
Topics:
Image Analysis,
Machine Learning,
Models:
Fuzzy ARTMAP,
Modified ART, |
| Author(s) |
Grossberg, S. |
Huang, T.R. |
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| Abstract |
How do humans rapidly recognize a scene? How can neural models capture this biological competence to achieve state-of-the-art scene classification? The ARTSCENE neural system
classifies natural scene photographs by using ... |
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| Categories |
Topics:
Speech and Hearing,
Applications:
Human-Machine Interface,
Models:
Fuzzy ARTMAP, |
| Author(s) |
Ames, H. |
Grossberg, S. |
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| Abstract |
Auditory signals of speech are speaker dependent, but representations of language meaning are speaker independent. The transformation from speaker-dependent to speaker-independent language representations enables speech to ... |
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| Categories |
Topics:
Image Analysis,
Models:
Boundary Contour System, |
| Author(s) |
Grossberg, S. |
Pilly, P.K. |
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| Abstract |
How does the brain make decisions? Speed and accuracy of perceptual decisions covary with certainty in the input, and correlate with the rate of evidence accumulation in parietal and frontal cortical ?decision neurons.? A ... |
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| Categories |
Topics:
Image Analysis,
Applications:
Information Fusion,
Models:
ARTMAP, |
| Author(s) |
Carpenter, G.A. |
Ravindran, A. |
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| Abstract |
Sensors working at different times, locations, and scales, and experts with different goals, languages, and situations, may produce apparently inconsistent image labels that are reconciled by their implicit underlying ... |
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| Categories |
Topics:
Neural Hardware,
Other,
Models:
Compartmental Modeling, |
| Author(s) |
Ames, H. |
Gorchetchnikov, A. |
Jasmin Leveille |
Versace, M. |
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| Abstract |
Making use of very detailed neurophysiological, anatomical, and behavioral data to build biologically-realistic computational models of animal behavior is often a difficult task. Until recently, many software packages have ... |
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| Categories |
Topics:
Biological Learning,
Models:
Modified ART, |
| Author(s) |
Grossberg, S. |
Versace, M. |
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| Abstract |
This article develops the Synchronous Matching Adaptive Resonance Theory (SMART) neural model to explain how the brain may coordinate multiple levels of thalamocortical and corticocortical processing to rapidly learn, and ... |
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