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Titlebook: Document Analysis and Recognition - ICDAR 2023; 17th International C Gernot A. Fink,Rajiv Jain,Richard Zanibbi Conference proceedings 2023

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Context-Aware Chart Element Detection in the general image domain, chart element detection relies heavily on context information as charts are highly structured data visualization formats. To address this, we propose a novel method ., which stands for .ontext-.ware .art .lement .etection, by integrating a local-global context fusion mo
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New Frontiers in Translation Studiesreal-world structure diagrams using the preliminary model and then making few manual corrections. Finally, we experimentally verified the significant performance advantage of our structure diagram recognition method over previous methods.
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New Frontiers in Translation Studiesocuments, and benchmark it on our novel FIR dataset. Our framework used Encoder-Decoder architecture for localizing and labelling the form fields and for recognizing the handwritten content. The encoder consists of Faster-RCNN and Vision Transformers. Further the Transformer-based decoder architectu
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Ali Jalalian Daghigh,Mark Shuttleworthd structures are used for better user experience and readability. The resulting model is compact, explainable and end-to-end trainable. The proposed technique outperforms the state-of-the-art algorithms in terms of binarization accuracy and successfully extracted information rates.
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Cultural Profiling for Translation Purposese-of-the-art in both datasets, achieving a word recognition rate of . and a 2.41 DTW on IRONOFF and an expression recognition rate of . and a DTW of 13.93 on CROHME 2019. This work constitutes an important milestone toward full offline document conversion to online.
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https://doi.org/10.1007/978-981-13-6343-6our approach, we create character segmentation ground truths for two popular on-line handwriting datasets, IAM-OnDB and HANDS-VNOnDB, and evaluate multiple methods on them, demonstrating that our approach achieves the overall best results.
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