Shape representations for learning perceptual properties
Learning viewpoint invariant perceptual representations from cluttered images
... of learning to develop invariant object ...enables learning to succeed when the training environment contains multiple, co-occurring, ...biases learning so that coincident objects will be represented ...
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Learning viewpoint invariant perceptual representations from cluttered images
... of learning invariance to ...to learning invariant perceptual representations under other forms of ...for learning different bar orientations invariant to ...
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Learning Invariant Visual Shape Representations from Physics
... ject representations cluster roughly equidistantly, ...for learning from few examples, either supervised (as shown in the central subplot of ...object shape can not trivially be clustered in the ...
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Action-related properties of objects shape object representations in the ventral stream
... Thus, two broad properties of the organization of the human visual system can be distinguished. On the one hand, visually presented objects are processed in the ventral stream for recognition and in the dorsal ...
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Helmholtz on Perceptual Properties
... Helmholtz maintains that sensations can enter into a relation to objects distinct from them—what he calls the “sign [Zeichen]” relation. Readers of Helmholtz broadly agree that unlike what he calls “images,” sensation ...
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Shape Representations for Object Recognition
... 4 Shape-based Detection in Videos Many view-point invariant object recognition approaches rely on learning a 2D bag of features or feature constellations from a set of limited views as ...general, ...
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From perceptual to semantic representations in the human brain
... concept learning by means of pattern separation and pattern completion, that allow to differentiate overlapping experiences for behavioural purposes, as well as integrating those aspects of these experiences that ...
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Shape Representations Using Nested Descriptors
... This argument is not limited to SVMs. Any discriminative classifier that learns a classification function in a fixed feature space is learning a categorization rule. This is true by construction, since a ...
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Multiple Representations of Perceptual Features for Texture Classification and Retrieval
... Busyness was estimated based on coarseness. These four basic properties of texture were conceptually defined. The conceptual expressions were put into computational forms. In this approach, autocorrelation ...
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Learning shape-to-shape transformation
... of shape transform In image translation, pixel values are stored on a regular ...3D shape is a set of 2D manifolds, or a set of points on the 2D manifolds after discretizing it by ...sampling. Shape ...
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Deep Shape Representations for 3D Object Recognition
... Deep Shape-Aware Descriptor for 3D Object Retrieval Deep learning has become a pervasive and wide reaching technology, growing at a breathtaking rate and achieving remarkable results on a variety of fields, ...
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Learning Representations in Reinforcement Learning
... distributed representations, this kWTA mech- anism has two properties that are worthy of ...small learning rate would keep these deviations ...the learning algorithm with some flexibility, ...
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Perceptual learning in Vision Research
... the perceptual learning studies of recent years is that understand- ing the mechanisms of learning within perceptual systems is a tractable ...Importantly, perceptual learning ...
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BAS: A Perceptual Shape Descriptor Based on the Beam Angle Statistics
... two representations. 6. Conclusion This study introduces a robust shape descriptor for identifying the similar objects in an image ...the perceptual information using the statistical information ...
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Semantic, Cognitive, and Perceptual Computing: Paradigms That Shape Human Experience
... Cognitive algorithms, a major focus of current CC research, interpret data by learning and matching patterns in a way that approximates human cognition. CC systems, another research area, use machine ...
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Autonomous Learning of Representations
... similar shape and parameterization leads to topological objects which re- semble a fractal nature and self-similarity, a principle which is well known in the context of recurrent networks ...
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Learning Transferable Representations
... that learning representations which exploit causal properties of the data generating process leads to attractive properties for transfer when the training and test distributions ...statistical ...
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Size-sensitive perceptual representations underlie visual and haptic object recognition.
... Half of the participants performed the experiment visually on photographs of the objects; the other half performed it haptically on the real objects while blindfolded. Size changes were similarly disruptive for both ...
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A feedback model of perceptual learning and categorisation
... Perception; Learning; Neural Networks; ...underly perceptual processes. Furthermore, changes in the response properties of such neurons underly changes in perceptual abilities (Karni, 1996; ...
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Generalization of Perceptual Learning of Vocoded Speech
... Talker-specific learning effects are con- sistent with episodic models that allow for indexical information to influence ...ceptual learning can generalize between different lexical items (see ...
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