ABSTRACT. Previous work on unsupervised learning has shown that it is possible to learn Gabor-like feature representations, similar to those employed in the ...
Bilinear models of natural images and their application to image analysis. David K. Warland, PI. Bruno A. Olshausen, co-PI. Jack Culpepper, graduate student.
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Recent algorithms for sparse coding and independent component analy- sis (ICA) have demonstrated how localized features can be learned from natural images.
We present results demonstrating bilinear sparse coding of natural images. We also explore an extension of the model that can capture spatial relationships ...
To render an image of a particular person in a particular pose, a set of I × J basis images wij is linearly mixed with coefficients given by the tensor product ...
redundan y in the image ode and provides a basis for transformation- invariant vision. We present results demonstrating bilinear sparse oding of natural images.
Our images are simple compared to natural images but contain sufficient ... within three-dimensional linear models of natural surfaces and illuminants.
Bilinear models have been proposed to separate the factors from the observations for joint factors identification or translation tasks.
This paper proposes a novel deep learning model called bilinear deep belief network (BDBN) for image classification. Unlike previous image classification models ...