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Learning to detect, localize and recognize many text objects in document images from few examples.

, , и . Int. J. Document Anal. Recognit., 21 (3): 161-175 (2018)

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The A2iA Multi-lingual Text Recognition System at the Second Maurdor Evaluation., , , , , , и . ICFHR, стр. 297-302. IEEE Computer Society, (2014)Learning to detect and localize many objects from few examples., , и . CoRR, (2016)Space Displacement Localization Neural Networks to locate origin points of handwritten text lines in historical documents., , , и . HIP@ICDAR, стр. 1-8. ACM, (2015)relocated from Gammarth, Tunisia.Paragraph text segmentation into lines with Recurrent Neural Networks., , , и . ICDAR, стр. 456-460. IEEE Computer Society, (2015)relocated from Tunis, Tunisia.Manifold Mixup Improves Text Recognition with CTC Loss., и . ICDAR, стр. 799-804. IEEE, (2019)Adversarial Generation of Handwritten Text Images Conditioned on Sequences., , и . ICDAR, стр. 481-486. IEEE, (2019)Automatic Line Segmentation and Ground-Truth Alignment of Handwritten Documents., , и . ICFHR, стр. 667-672. IEEE Computer Society, (2014)Are 2D-LSTM really dead for offline text recognition?, и . CoRR, (2018)Full-Page Text Recognition: Learning Where to Start and When to Stop., , и . ICDAR, стр. 871-876. IEEE, (2017)A Comparison of Recognition Strategies for Printed/Handwritten Composite Documents., , и . ICFHR, стр. 158-163. IEEE Computer Society, (2014)