Results 281 to 290 of about 1,098,703 (325)

Phase Oscillatory Network and Visual Pattern Recognition

IEEE Transactions on Neural Networks and Learning Systems, 2015
We explore a properly interconnected set of Kuramoto type oscillators that results in a new associative-memory network configuration, which includes second- and third-order additional terms in the Fourier expansion of the network's coupling. Investigation of the response of the network to different external stimuli indicates an increase in the network ...
Elbert E. N. Macau, Epaminondas Rosa, Rosangela Follmann, José Roberto Castilho Piqueira   +3 more
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Signal transformation and pattern recognition in visual pathways [PDF]

Biological Cybernetics, 1976
A model of the visual pathways it has been developed consisting of two neural systems working together: a feed-forward mechanism given by convolutions through different layers and a feed-back one consiting of the comparison of the results of the first one.
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Pattern Recognition with the Optic Nerve Visual Prosthesis

Artificial Organs, 2003
Abstract:  A volunteer with retinitis pigmentosa and no residual vision was chronically implanted with an optic nerve electrode connected to an implanted neurostimulator and antenna. An external controller with telemetry was used for electrical activation of the nerve which resulted in phosphene perception.
Claude Veraart, Benoît Gérard, Annick Vanlierde, Jean Delbeke, Marie-Chantal Wanet-Defalque   +4 more
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Light adaptation for visual pattern recognition in flies

Vision Research, 1973
Abstract Flies were found to possess the light adaptation phenomena of vertebrates whereby the eyes achieve optimal sensitivity to an intensity increment on a given background illumination. This was found in the photoreceptors and several higher levels including a behavioral response.
Gilbert D. McCann, Susan F. Foster
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Visual Pattern Recognition in Animals

1971
Some two thousand million years ago living organisms initiated the invention of means for detecting optical signals to be reacted to by purposeful actions. This decisive evolutionary step already took place at the primitive organizational level of the bacteria, as may be inferred from present life.
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A neural network for visual pattern recognition

Computer, 1988
A model of a neural network is presented that offers insight into the brain's complex mechanisms as well as design principles for information processors. The model has properties and abilities that most modern computers and pattern recognizers do not possess; pattern recognition, selective attention, segmentation, and associative recall.
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Studies on visual pattern recognition in man and animals

Vision Research, 1974
Abstract The investigation of the time characteristics of visual recognition in man and animals has revealed three types of recognition performance. The first and the third types are characterized by independence of the amount of information received of the time of its processing; the second type involves the linear relationship between these ...
V.D. Glezer, A.A. Nevskaya, L.I. Leushina, N.V. Prazdnikova   +3 more
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Visual pattern recognition by moment invariants

IEEE Transactions on Information Theory, 1962
In this paper a theory of two-dimensional moment invariants for planar geometric figures is presented. A fundamental theorem is established to relate such moment invariants to the well-known algebraic invariants. Complete systems of moment invariants under translation, similitude and orthogonal transformations are derived.
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Visual pattern memory without shape recognition

Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences, 1995
Visual pattern memory of Drosophila melanogaster at the torque meter is investigated by a new learning paradigm called novelty choice. In this procedure the fly is first exposed to four identical patterns presented at the wall of the cylinder surrounding it.
Marcus Dill, Martin Heisenberg
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An effective method for visual pattern recognition

Neural Networks for Signal Processing Proceedings of the 1991 IEEE Workshop, 2002
An effective method for neural network based visual pattern recognition is presented. It is shown that it can be successfully used for visual recognition of deformed letters. The main advantages of the presented method are its intuitive appeal, simple implementation and analytical justification. >
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