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:
Machine Learning,
Applications:
Information Fusion,
Remote Sensing,
Models:
ARTMAP, |
Author(s) |
Carpenter, G.A. |
Martens, S. |
Ogas, O. J. |
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Abstract |
Classifying novel terrain or objects from sparse, complex data may require the resolution of conflicting information from sensors working at different times, locations, and scales, and from sources with different goals and ... |
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Categories |
Topics:
Image Analysis,
Machine Learning,
Applications:
Information Fusion,
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Author(s) |
Carpenter, G.A. |
Chelian, S.F. |
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Abstract |
The DISCOV (DImensionless Shunting COlour Vision) system models a cascade of primate colour vision cells: retinal ganglion, thalamic single opponent, and two classes of cortical double opponents. A unified model formalism ... |
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Categories |
Topics:
Biological Vision,
Models:
Boundary Contour System, |
Author(s) |
Grossberg, S. |
Yazdanbakhsh, A. |
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Abstract |
Perceptual grouping is well known to be a fundamental process during visual perception, notably grouping across scenic regions that do not receive contrastive visual inputs. Illusory contours are a classical example of such ... |
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Categories |
Topics:
Image Analysis,
Applications:
Character Recognition,
Models:
Other, |
Author(s) |
Grossberg, S. |
Paine, R.W. |
Van Gemmert, A.W.A. |
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Abstract |
Much sensory-motor behavior develops through imitation, as during the learning of handwriting by children. Such complex sequential acts are broken down into distinct motor control synergies, or muscle groups, whose ... |
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Categories |
Topics:
Biological Vision,
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Author(s) |
Grossberg, S. |
Hong, S. |
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Abstract |
This study develops a neuromorphic model of human lightness perception that is inspired by how the mammalian visual system is designed for this function. It is known that biological visual representations can adapt to a ... |
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Categories |
Topics:
Machine Learning,
Speech and Hearing,
Models:
Modified ART, |
Author(s) |
Cohen, G.M. |
Govindarajan, K.K. |
Grossberg, S. |
Wyse, L.L. |
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Abstract |
Multiple sound sources often contain harmonics that overlap and may be degraded by environmental noise. The auditory system is capable of teasing apart these sources into distinct mental objects, or streams. Such an ... |
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Categories |
Topics:
Machine Learning,
Applications:
Financial Time Series Predictions,
Models:
Genetic Algorithms, |
Author(s) |
Bhatt, R. |
Hinds, O. |
Shiffer, M. |
Versace, M. |
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Abstract |
We evaluate the performance of a heterogeneous mixture of neural network algorithms for predicting the exchange-traded fund DIA. A genetic algorithm is utilized to find the best mixture of neural networks, the topology of ... |
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Categories |
Topics:
Biological Vision,
Machine Learning,
Models:
Other, |
Author(s) |
Carpenter, G.A. |
Martens, S. |
Mingolla, E. |
Ogas, O. J. |
Sai, C. |
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Abstract |
Ongoing research at Boston University has produced computational models of biological vision and learning that embody a growing corpus of scientific data and predictions. Vision models perform long-range grouping and ... |
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Categories |
Topics:
Biological Vision,
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Author(s) |
Grossberg, S. |
Swaminathan, G. |
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Abstract |
A model of laminar visual cortical dynamics proposes how 3D boundary and surface representations arise from viewing slanted and curved 3D objects and 2D images. The 3D boundary representations emerge from non-classical ... |
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Categories |
Topics:
Machine Learning,
Models:
Other, |
Author(s) |
Carpenter, G.A. |
Kopco, N. |
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Abstract |
A memory-based learning system called PointMap is introduced. The algorithm, an extension of Condensed Nearest Neighbor, evaluates the information value of coding nodes during training, and uses this index to prune ... |
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