Unsupervised Learning of Invariant Feature Hierarchies with Applications to Object Recognition MarcAurelio Ranzato FuJie Huang YLan Boureau Yann Le Cun Courant Institute of Mathematical Sciences New PDF document - DocSlides
nyuedu httpwwwcsnyuedu yann Abstract We present an unsupervised method for learning a hier archy of sparse feature detectors that are invariant to smal shifts and distortions The resulting feature extractor co n sists of multiple convolution 64257lte ID: 24749Embed code:
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