Titlebook: Document Analysis Systems; 14th IAPR Internatio Xiang Bai,Dimosthenis Karatzas,Daniel Lopresti Conference proceedings 2020 Springer Nature

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Approach to the Adult Hypospadias Patientype of data that is used for training. In the presence of diverse style in the document images (eg. fonts, print, writer, imaging process), creating a large amount of training data is impossible. In this paper, we explore the problem of adapting an existing OCR, already trained for a specific collec

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https://doi.org/10.1007/978-981-16-8603-0he Linguistic Atlas of France (ALF) maps are composed of printed phonetic words used to locate how words were pronounced over the country. Those words were printed using the Rousselot-Gillieron alphabet (extension of Latin alphabet) which bring character recognition problems due to the large number

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Funktionelle neurologische St?rungenearch is suggested for solving complex document analysis studies. However, improving performance by adding U-Net modules requires using too many parameters in cascaded U-Nets. Therefore, in this paper, we propose a method for enhancing the performance of cascaded U-Nets. We suggest a novel document

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https://doi.org/10.1057/9780230244986 In this paper, we propose a novel framework for both rectifying distorted document image and removing background finely, by estimating pixel-wise displacements using a fully convolutional network (FCN). The document image is rectified by transformation according to the displacements of pixels. The

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Shinichi Ichimura,Tsuneaki Satoacter recognition (OCR) accuracy. However, even despite the ill-posed nature of image super-resolution (SR) problem, how do we treat the finer details of text with large upscale factors and suppress noises and artifacts at the same time, especially for low quality document images is still a challeng