Learning and disrupting invariance in visual recognition with a temporal association rule

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Unsupervised Natural Visual Experience Rapidly Reshapes Size-Invariant Object Representation in Inferior Temporal Cortex

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View-based Models of 3D Object Recognition: Invariance to Imaging Transformations

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Learning viewpoint invariant object representations using a temporal coherence principle

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Why The Brain Separates Face Recognition From Object Recognition

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Unsupervised Learning of Invariant Representations in Hierarchical ArchitecturesPreprint

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A specialized face-processing model inspired by the organization of monkey face patches explains several face-specific phenomena observed in humans

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The Invariance Hypothesis Implies Domain-Specific Regions in Visual Cortex

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Finding and recognizing objects in natural scenes: complementary computations in the dorsal and ventral visual systems

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Unsupervised changes in core object recognition behavior are predicted by neural plasticity in inferior temporal cortex

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Spatiotemporal information during unsupervised learning enhances viewpoint invariant object recognition

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Deformation-specific and deformation-invariant visual object recognition: pose vs. identity recognition of people and deforming objects

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Invariant Recognition Predicts Tuning of Neurons in Sensory Cortex

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Computational modeling of the neural representation of object shape in the primate ventral visual system

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Remarks on Invariance in the Primary Visual Systems of Mammals

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The invariance hypothesis and the ventral stream

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Unsupervised changes in core object recognition behavior are predicted by neural plasticity in inferior temporal cortexPreprint

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How Shape Perception Works, in Two Dimensions and Three Dimensions

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Cortical Networks of Visual Recognition

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A specialized face-processing network consistent with the representational geometry of monkey face patchesPreprint

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What happens next and when "next" happens: Mechanisms of spatial and temporal predictionPreprint

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Face Recognition Using Invariance with a Single Training Sample

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Exploiting temporal continuity of views to learn visual object invariance

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Maximum Value of the Symmetrical Diagonal Matrix Based Two - Dimensional Eigenface s for Facial Recognition on the Variant Lighting and Expressions

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Biasing restricted Boltzmann machines using Gaussian filters to learn invariant visual features

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Faculty Opinions recommendation of Toward a unified model of face and object recognition in the human visual system.

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Tomaso A. Poggio

(2014) · Society for Neuroscience eBooks · doi:10.1523/hon.008009

Learning and disrupting invariance in visual recognition

Işık, L., Leibo, J. Z., & Poggio, T. (2011) · DSpace@MIT (Massachusetts Institute of Technology) · Cited by 1 · see citing works

massachusetts institute of technology, cambridge, ma 02139 usa — www.csail.mit.eduLearning and disrupting invariance in visual recognition

Işık, L., Leibo, J. Z., & Poggio, T. (2011)

COMPUTATIONAL NEUROSCIENCE ORIGINAL RESEARCH ARTICLE

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Learning invariance in visual perception.

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Invariant Object Recognition in the Visual System with . . .

Rolls, & Stringer, S. M. (2001)