Search results for "Autoassociative memory"

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What represents a face? A computational approach for the integration of physiological and psychological data.

1997

Empirical studies of face recognition suggest that faces might be stored in memory by means of a few canonical representations. The nature of these canonical representations is, however, unclear. Although psychological data show a three-quarter-view advantage, physiological studies suggest profile and frontal views are stored in memory. A computational approach to reconcile these findings is proposed. The pattern of results obtained when different views, or combinations of views, are used as the internal representation of a two-stage identification network consisting of an autoassociative memory followed by a radial-basis-function network are compared. Results show that (i) a frontal and a…

050109 social psychologyExperimental and Cognitive PsychologyFacial recognition system050105 experimental psychologyAutoassociative memoryConnectionismArtificial IntelligenceMemoryImage Processing Computer-AssistedHumans0501 psychology and cognitive sciencesComputer SimulationRecognition memoryCommunicationArtificial neural networkbusiness.industryMemoria05 social sciencesCognitionSensory SystemsForm PerceptionOphthalmologyIdentification (information)FacePsychologybusinessCognitive psychologyPerception
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Sex Classification of Face Areas

1998

Human subjects and an artificial neural network, composed of an autoassociative memory and a perceptron, gender classified the same 160 frontal face images (80 male and 80 female). All 160 face images were presented under three conditions (1) full face image with the hair cropped (2) top portion only of the Condition 1 image (3) bottom portion only of the Condition 1 image. Predictions from simulations using Condition 1 stimuli for training and testing novel stimuli in Conditions 1, 2, and 3, were compared to human subject performance. Although the network showed a fair ability to generalize learning to new stimuli under the three conditions, performing from 66 to 78% correctly on novel fa…

Image areaEcologyArtificial neural networkComputer sciencebusiness.industryApplied MathematicsPattern recognitionGeneral MedicinePerceptronAgricultural and Biological Sciences (miscellaneous)Image (mathematics)Autoassociative memoryFace (geometry)Human taxonomyRelevance (information retrieval)Artificial intelligencebusinessJournal of Biological Systems
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