Abstract
In this paper, we present an Optical Character Recognition (OCR) system specifically designed for the accurate recognition and digitization of Greek polytonic texts. By leveraging the combined strengths of convolutional layers for feature extraction and recurrent layers for sequence learning, our system addresses the unique challenges posed by Greek polytonic scripts. This approach aims to overcome the limitations of traditional OCR methods, offering significant improvements in accuracy and efficiency. We release the underlying model as an open-source library and make our OCR platform available for academic use.
Abstract (translated)
在这篇论文中，我们提出了一种专门用于准确识别和数字化希腊多音调文本的光学字符识别（OCR）系统。通过利用卷积层进行特征提取和递归层进行序列学习的综合优势，我们的系统解决了由希腊多音调脚本带来的独特挑战。这种方法旨在克服传统OCR方法的局限性，在准确性和效率方面提供了显著改进。我们将基础模型作为开源库发布，并将我们的OCR平台提供给学术界使用。
URL
https://arxiv.org/abs/2506.21474
