Results 211 to 220 of about 183,987 (263)
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A VISUAL MODEL FOR PATTERN RECOGNITION
International Journal of Neural Systems, 1992A general model for an optical recognition system capable of simultaneous recognition of patterns at different resolution levels is outlined. The model is based on two hierarchic stages of processing networks and presents interesting analogies with the human visual system. Illustrative applications and preliminary experimental results are also briefly
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Compression for visual pattern recognition
2008 3rd International Symposium on Communications, Control and Signal Processing, 2008To date, computer science solves pattern recognition problems by highly task specific algorithms. Searching for a generic, unifying principle of pattern recognition, Benedetto et al. showed that compression is a good candidate: For the domain of text, approximating the mutual information of patterns by the achievable compression factors allows to ...
Gunther Heidemann, Helge Ritter
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Semantics of the recognition of visual patterns
Journal of Optical Technology, 2011This article compares external real objects (images, video) with the internal world of their semantic representation. An algorithm is proposed for semantic learning and the recognition of visual patterns. A definition is given of the concept of “intelligent optics.” The world is not everything that can be (not Infinitum, but Indeterminatum).
V. V. Alexandrov +2 more
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A neural network for visual pattern recognition
Computer, 1988A 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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Spiking neural network for visual pattern recognition
2014 International Conference on Multisensor Fusion and Information Integration for Intelligent Systems (MFI), 2014Most of visual pattern recognition algorithms try to emulate the mechanism of visual pathway within the human brain. Regarding of classic face recognition task, by using the spatiotemporal information extracted from Spiking neural network (SNN), batch learning rule and on-line learning rule stand out from their competitors.
Daqi Liu, Shigang Yue
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Pattern Recognition for Automatic Visual Inspection
Computer, 1982Three major approaches to pattern recognition, (1) template matching, (2) decision-theoretic approach, and (3) structural and syntactic approach, are briefly introduced. The application of these approaches to automatic visual inspection of manufactured products are then reviewed. A more general method for automatic visual inspection of IC chips is then
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Learning optimal features for visual pattern recognition
SPIE Proceedings, 2007The optimal coding hypothesis proposes that the human visual system has adapted to the statistical properties of the environment by the use of relatively simple optimality criteria. We here (i) discuss how the properties of different models of image coding, i.e.
Kai Labusch +3 more
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Phase Oscillatory Network and Visual Pattern Recognition
IEEE Transactions on Neural Networks and Learning Systems, 2015We 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 ...
Rosangela Follmann +3 more
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Recognition of visual pattern components in squirrel monkeys
European Archives of Psychiatry and Neurological Sciences, 1986In 4 mixed-age captive groups of squirrel monkeys the predator alarm behavior control by means of visual stimuli was studied, and the extent to which socially inexperienced infant squirrel monkeys are capable of species-specific alarm behavior. By means of color film projection it was shown that both the socially experienced and inexperienced subjects ...
M, Herzog, S, Hopf
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Visual pattern recognition with neural networks
1992The “neocognitron” was first proposed as a hierarchical neural network model for the mechanism of visual pattern recognition in the brain. It is capable of deformation-resistant pattern recognition. Various experiments have demonstrated its powerful ability to recognize visual patterns.
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