Recurrent Models of Visual Attention

NeurIPS 2014 Volodymyr MnihNicolas HeessAlex GravesKoray Kavukcuoglu

Applying convolutional neural networks to large images is computationally expensive because the amount of computation scales linearly with the number of image pixels. We present a novel recurrent neural network model that is capable of extracting information from an image or video by adaptively selecting a sequence of regions or locations and only processing the selected regions at high resolution... (read more)

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