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,
Machine Learning,
Models:
ART 1,
ART 2 / Fuzzy ART,
ARTMAP,
Fuzzy ARTMAP, |
| Author(s) |
Carpenter, G.A. |
Grossberg, S. |
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| Abstract |
Principles derived from an analysis of experimental literatures in vision, speech, cortical development, and reinforcement learning, including attentional blocking and cognitive-emotional interactions, led to the ... |
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| Categories |
Topics:
Machine Learning,
Models:
ART 2 / Fuzzy ART, |
| Author(s) |
Carpenter, G.A. |
Grossberg, S. |
Rozen, D.B. |
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| Abstract |
An improved ART2 network provides fast and intermediate learning. The network combines analog and binary coding functions. The analog portion encodes the recent past while the binary portion retains the distant past. LTM ... |
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| Categories |
Topics:
Biological Vision,
Models:
Boundary Contour System,
Other, |
| Author(s) |
Grossberg, S. |
Hwang, S. |
Mingolla, E. |
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| Abstract |
This article further develops the FACADE neural model of 3-D vision and figure-ground perception to quantitatively explain properties of the McCollough effect (ME). The model proposes that many ME data result from visual ... |
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| Categories |
Topics:
Biological Vision,
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| Author(s) |
Grossberg, S. |
Grunewald, A. |
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| Abstract |
A neural model is developed to probe how corticogeniculate feedback may contribute to the dynamics of binocular vision. Feedforward and feedback interactions among retinal, lateral geniculate, and cortical simple and complex ... |
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| Categories |
Topics:
Image Analysis,
Models:
Boundary Contour System, |
| Author(s) |
Dresp, B. |
Durand, S. |
Grossberg, S. |
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| Abstract |
The experiments reported herein probe the visual cortical mechanisms that control near-far percepts in response to two-dimensional stimuli. Figural contrast is found to be a principal factor for the emergence of percepts of ... |
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| Categories |
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| Author(s) |
Carpenter, G.A. |
Milenova, B. |
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| Abstract |
Markram and Tsodyks, by showing that the elevated synaptic efficacy observed with single-pulse long-term potentiation (LTP) measurements disappears with higher-frequency test pulses, have critically challenged the ... |
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| Categories |
Topics:
Image Analysis,
Applications:
Information Fusion,
Other,
Models:
Other, |
| Author(s) |
McKenna, T.S. |
Rhodes, B.J. |
Waxman, A.M. |
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| Abstract |
In support of the AFOSR program in Information Fusion, the CNS Technology Laboratory at Boston University is developing and applying neural models of image and signal processing, pattern learning and recognition, associative ... |
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| Categories |
Topics:
Biological Vision,
Machine Learning,
Models:
Boundary Contour System,
Other, |
| Author(s) |
Grossberg, S. |
Raizada, R. |
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| Abstract |
A detailed neural model is presented of how the laminar circuits of visual cortical areas V1 and V2 implement context-sensitive binding processes such as perceptual grouping and attention. The model proposes how specific ... |
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| Categories |
Topics:
Biological Learning,
Biological Vision,
Other,
Models:
Other, |
| Author(s) |
Grossberg, S. |
Mingolla, E. |
Pack, C. |
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| Abstract |
Smooth pursuit eye movements (SPEMs) are eye rotations that are used to maintain fixation on a moving target. Such rotations complicate the interpretation of the retinal image, because they nullify the retinal motion of the ... |
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| Categories |
Topics:
Biological Vision,
Models:
Other, |
| Author(s) |
Grossberg, S. |
Mingolla, E. |
Viswanathan, L. |
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| Abstract |
A neural model is developed of how motion integration and segmentation processes, both within and across apertures, compute global motion percepts. Figure-ground properties, such as occlusion, influence which motion signals ... |
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