Fully Convolutional Neural Networks for Page Segmentation of Historical Document Images

21 Nov 2017 Christoph Wick Frank Puppe

We propose a high-performance fully convolutional neural network (FCN) for historical document segmentation that is designed to process a single page in one step. The advantage of this model beside its speed is its ability to directly learn from raw pixels instead of using preprocessing steps e. g. feature computation or superpixel generation... (read more)

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