Titlebook: Document Analysis and Recognition - ICDAR 2024; 18th International C Elisa H. Barney Smith,Marcus Liwicki,Liangrui Peng Conference proceedi

MAL

n and recognition using the same backbone, with the detection branch based on multiple deep layers and the recognition branch based on multiple shallow layers, thereby constructing an end-to-end detection and recognition network. Comparative experiments on CCPD and RodoSol datasets validate that our

Resistance

Weibo Luo,Yingfei Wang,Georg Reiser*etween the ground-truth and the CP-predicted image. Experimental results on four public benchmark images demonstrate that our method surpasses state-of-the-art methods in the task of highlight removal.

媒介

機械

腐蝕

he potential error recognition results, offering a low-cost yet effective solution. Experimental results on different radical-based CCR models and datasets demonstrate the effectiveness and robustness of our proposed method.

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MORT

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即席演說

0302-9743 ICDAR 2024, held in Athens, Greece, during August 30–September 4, 2024..The total of 144 full papers presented in these proceedings were carefully selected from 263 submissions..The papers reflect topics such as: Document image processing; physical and logical layout analysis; text and symbol recog