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Self-organizing neural network that discovers surfaces in random-dot stereograms

Authors: Suzanna Becker, Geoffrey E. Hinton - Nature 1992 cited by 508

Learning Representationsby Back-Propagating…Learning Representations by Back-Propagating ErrorsNeural model ofstereoacuity and depth…Neural model of stereoacuity and depth interpolation based on a distributed representation of stereo disparity [published erratum appears in J Neurosci 1991 Mar;11(3):following Table of Contents]Generalized AdditiveModels.Generalized Additive Models.Generalized AdditiveModels.Generalized Additive Models.Advances in neuralinformation processing…Advances in neural information processing systems 7Neural Networks andRelated Methods for…Neural Networks and Related Methods for ClassificationThe Helmholtz machineThe Helmholtz machineCategory LearningThrough Multi-Modality…Category Learning Through Multi-Modality SensingLearning with two sitesof synaptic integrationLearning with two sites of synaptic integrationCortical RegionInteractions and the…Cortical Region Interactions and the Functional Role of Apical DendritesA Theory of ObjectRecognition…A Theory of Object Recognition: Computations and Circuits in the Feedforward Path of the Ventral Stream in Primate Visual CortexNeural scenerepresentation and…Neural scene representation and renderingDark Experience forGeneral Continual…Dark Experience for General Continual Learning: a Strong, Simple BaselineRecent advances andclinical applications o…Recent advances and clinical applications of deep learning in medical image analysisHow to RepresentPart-Whole Hierarchies…How to Represent Part-Whole Hierarchies in a Neural NetworkMasked Autoencoders AreScalable Vision LearnersMasked Autoencoders Are Scalable Vision LearnersArtificial IntelligenceEnhanced Molecular…Artificial Intelligence Enhanced Molecular SimulationsSelf-organizing neuralnetwork that discovers…Self-organizing neural network that discovers surfaces in random-dot stereogramsEarlier referencesFocus paperCiting papersOlderNewer

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