Apr 27, 2018 · In this paper, we address multiple tasks simultaneously such as page extraction, baseline extraction, layout analysis or multiple typologies of ...
dhSegment is a tool for Historical Document Processing. Its generic approach allows to segment regions and extract content from different type of documents.
In this paper, we address multiple tasks simultaneously such as page extraction, baseline extraction, layout analysis or multiple typologies of illustrations ...
From an input image, the generic neural net- work (dhSegment) outputs probabilities maps, which are then post-processed to obtain the desired output for each ...
It is a generic approach for Historical Document Processing. It relies on a Convolutional Neural Network to do the heavy lifting of predicting pixelwise ...
This paper proposes an open-source implementation of a CNN-based pixel-wise predictor coupled with task dependent post-processing blocks.
Apr 27, 2018 · Key in this approach is the sharing of components, modules and other assets across a family of products. Current research indicates that ...
dhSegment : A generic deep-learning approach for document segmentation. Ares Oliveira, Sofia. •. Seguin, Benoît Laurent Auguste.
A Generic Deep-Learning Approach for Document Segmentation
www.researchgate.net › publication › 32...
Additionally, Oliveira et al. [7] introduced a dhSegment, which can handle pixelwise segmentation tasks on historical documents, including page and border ...
In this Academy, we introduce and show the functioning of dhSegment, an open-source implementation of a CNN-based pixel-wise predictor, coupled with task ...