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Bilinear models of natural images
2007
Human Vision and Electronic Imaging XII
Previous work on unsupervised learning has shown that it is possible to learn Gabor-like feature representations, similar to those employed in the primary visual cortex, from the statistics of natural images. However, such representations are still not readily suited for object recognition or other high-level visual tasks because they can change drastically as the image changes to due object motion, variations in viewpoint, lighting, and other factors. In this paper, we describe how bilinear
doi:10.1117/12.715515
dblp:conf/hvei/OlshausenCCW07
fatcat:xe35pjhiubfubigtdgnau534xa