Learning Hierarchical Image Representation with Sparsity, Saliency and Locality
نویسندگان
چکیده
We present a deep learning model for hierarchical image representation in which we build the hierarchy by stacking up the base models layer by layer. In each layer, the base model receives the features of the lower layer as input and produces a more invariant and complex representation. The bottom layer receives raw images as input and the top layer produces an image representation that can be used for high-level vision tasks.
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تاریخ انتشار 2011