LocalNorm: Robust Image Classification through Dynamically Regularized Normalization

18 Feb 2019Bojian YinSiebren SchaafsmaHenk CorporaalH. Steven ScholteSander M. Bohte

While modern convolutional neural networks achieve outstanding accuracy on many image classification tasks, they are, compared to humans, much more sensitive to image degradation. Here, we describe a variant of Batch Normalization, LocalNorm, that regularizes the normalization layer in the spirit of Dropout while dynamically adapting to the local image intensity and contrast at test-time... (read more)

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