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Visual Object Recognition [PDF]

open access: possibleAnnual Review of Neuroscience, 1996
Visual object recognition is of fundamental importance to most animals. The diversity of tasks that any biological recognition system must solve suggests that object recognition is not a single, general purpose process. In this review, we consider evidence from the fields of psychology, neuropsychology, and neurophysiology, all of which supports the ...
Logothetis, N., Sheinberg, D.
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Object recognition and visual object agnosia

2021
The term visual agnosia is used to refer to recognition disorders that are confined to the visual modality, that are not due to an impairment in sensory functions, and that cannot be explained by other cognitive deficits or by general reduction in intellectual ability.
Gerlach, Christian, Robotham, Ro Julia
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Object Reading: Text Recognition for Object Recognition

2012
We propose to use text recognition to aid in visual object class recognition. To this end we first propose a new algorithm for text detection in natural images. The proposed text detection is based on saliency cues and a context fusion step. The algorithm does not need any parameter tuning and can deal with varying imaging conditions. We evaluate three
Karaoglu, S.   +2 more
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Models of object recognition

Current Opinion in Neurobiology, 1991
Progress in the understanding of visual recognition in the past year has been signified by the demonstration of computational feasibility of and psychophysical support for two-dimensional view-interpolation methods.
Shimon Edelman, Tomaso Poggio
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Object recognition is not predication

Behavioral and Brain Sciences, 2003
Predicates involved in language and reasoning are claimed to radically differ from categories applied to objects. Human predicates are the cognitive result of a contrast between perceived objects. Object recognition alone cannot generate such operations as modification and explicit negation.
Jean-Louis Dessalles, Laleh Ghadakpour
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Models of object recognition

Nature Neuroscience, 2000
Understanding how biological visual systems recognize objects is one of the ultimate goals in computational neuroscience. From the computational viewpoint of learning, different recognition tasks, such as categorization and identification, are similar, representing different trade-offs between specificity and invariance.
Maximilian Riesenhuber, Tomaso Poggio
openaire   +3 more sources

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