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

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樓主: Sediment
21#
發(fā)表于 2025-3-25 05:15:22 | 只看該作者
Shinichi Ichimura,Tsuneaki Satority and monotonicity to predict the quality of document images. Based on the proposed network along with the new losses, the obtained DCNN achieves the state-of-the-art quality assessment performance on the public datasets. The source codes and pre-trained models are available at ..
22#
發(fā)表于 2025-3-25 09:28:57 | 只看該作者
23#
發(fā)表于 2025-3-25 11:50:57 | 只看該作者
24#
發(fā)表于 2025-3-25 18:55:06 | 只看該作者
Adapting OCR with Limited Supervisionii) Fine Tuning?+?Self Training. We discuss details on how these popular approaches in Machine Learning can be adapted to the text recognition problem of our interest. We hope, our empirical observations on two different languages will be of relevance to wider use cases in text recognition.
25#
發(fā)表于 2025-3-25 22:48:29 | 只看該作者
26#
發(fā)表于 2025-3-26 01:17:04 | 只看該作者
27#
發(fā)表于 2025-3-26 07:37:12 | 只看該作者
Dewarping Document Image by Displacement Flow Estimation with Fully Convolutional Networkth Constraint (LSC) in regularization. Our approach is easy to implement and consumes moderate computing resource. Experiments proved that our approach can dewarp document images effectively under various geometric distortions, and has achieved the state-of-the-art performance in terms of local details and overall effect.
28#
發(fā)表于 2025-3-26 10:45:57 | 只看該作者
29#
發(fā)表于 2025-3-26 16:26:49 | 只看該作者
Conference proceedings 2020wing topical sections: character and text recognition; document image processing; segmentation and layout analysis; word embedding and spotting; text detection; and font design and classification..Due to the Corona pandemic the conference was held as a virtual event ..
30#
發(fā)表于 2025-3-26 20:35:03 | 只看該作者
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