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

Charade

seruting

C. G. Gottfries,Rolf Adolfsson,Bengt Winbladtaset with 43.02% improvement, 2.94% on RIMES dataset with 56.25% improvement and 7.35% on READ-2016 dataset with 47.27% improvement from the existing results. The character error rate and word error rate reported in this work surpass the results reported in the literature.

chemoprevention

Arxiv Tables: Document Understanding Challenge Linking Texts and?Tablesistinguishes the dataset is that (1) the domain is science, (2) the input texts are longer than in typical Document Understanding Question Answering tasks, and (3) both the input and output contain non-standard characters used in scientific notation. For easier comparison for future research using this dataset, strong baselines are also given.

GROWL

Text Line Detection and?Recognition of?Greek Polytonic Documentsrovide a new dataset to the public (GTLD-small) for text line detection. We evaluate our method through scenarios applied to the detection and recognition tasks, while demonstrating promising results when compared to popular commercial or open-source systems.

接合

無能力之人

Macmillan Motor Vehicle Engineering Serieshus it is purely a structure perception approach, not dependent on the language and the quality of the text reading. We evaluate our model on invoice-like documents and the proposed method showed good results for the task of table extraction.

ALIEN

尋找

E. S. Garnett,G. Firnau,C. Nahmiasges with more accurate style realization. This loss function has the merit of applicability to various font generation models. Our experimental results show that the proposed loss function improves the quality of generated character images by several few-shot font generation models.

Default

A Clustering Approach Combining Lines and?Text Detection for?Table Extractionhus it is purely a structure perception approach, not dependent on the language and the quality of the text reading. We evaluate our model on invoice-like documents and the proposed method showed good results for the task of table extraction.

創(chuàng)造性

A New Optimization Approach to Improve an Ensemble Learning Model: Application to Persian/Arabic Hanthm. The ensemble model is fed by a set of handcrafted features, including directional and intersection features, extracted from handwritten text. The proposed model is evaluated using three different datasets. Results obtained from the proposed models demonstrate higher accuracies compared to the state-of-the-art models.