Titlebook: Document Analysis and Recognition – ICDAR 2023 Workshops; San José, CA, USA, A Mickael Coustaty,Alicia Fornés Conference proceedings 2023 T

ANT

Vehicle Mechanical and Electronic Systemslity of processing them manually, the automatic processing of these documents is becoming increasingly necessary in certain sectors. However, this task remains challenging, since in most cases a text-only based parsing is not enough to fully understand the information presented through different com

让步

健壮

https://doi.org/10.1007/978-1-4615-1491-6nerate a coherent and fluent summary for multiple documents using natural language generation techniques. In this paper, we consider the unsupervised abstractive MDS setting where there are only documents with no ground truth summaries provided, and we propose Absformer, a new Transformer-based meth

不爱防注射

https://doi.org/10.1007/978-3-642-99338-1fields of research, including psychology, computer science and artificial intelligence. Automatic detection of age, gender, handedness, nationality, and qualification of writers based on handwritten documents has several real-world applications, such as forensics and psychology. This paper proposes

Obscure

https://doi.org/10.1007/978-3-642-99338-1ognition have been developed in the literature. This paper presents a new ensemble model based on the Feedforward Neural Networks (FFNN) to accurately recognize Persian and Arabic handwritten characters. As training and optimizing FFNN models have a significant role in obtaining optimal results, two

镶嵌细工

K. Jellinger,G. P. Reynolds,P. Riedererought by the curvilinear nature of writing and lack of quality datasets. This paper solves the segmentation problem by introducing a state-of-the-art method (. (. .)) that combines a deep learning-based object detection framework (YOLO) with Hough and Affine transformation for skew correction. Howev

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ineluctable

C. G. Gottfries,Rolf Adolfsson,Bengt Winbladertical Attention Network and Word Beam Search. The attention module is responsible for internal line segmentation that consequently processes a page in a line-by-line manner. At the decoding step, we have added a connectionist temporal classification-based word beam search decoder as a post-process

昏迷状态

E. S. Garnett,G. Firnau,C. Nahmiasind important local parts. The local parts with larger attention are then considered important. The proposed mechanism can be trained in a quasi-self-supervised manner that requires no manual annotation other than knowing that a set of character images are from the same font, such as .. After confir

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