论文标题
识别现代和历史手写的数字字符串的端到端方法
An End-to-End Approach for Recognition of Modern and Historical Handwritten Numeral Strings
论文作者
论文摘要
提出了用于手写数字字符串识别的端到端解决方案，其中数字字符串被认为是由基于Yolo的模型自动检测和识别的对象组成的。本文的主要贡献是避免基于启发式的方法用于字符串的预处理和分割，需要以任务为导向的分类器以及使用与字符串长度相关的特定约束。基于几个数字字符串数据集的强大实验协议，包括由历史文档组成的数据集，它表明该方法是用于数字字符串识别的可行端到端解决方案。此外，它可以大大降低字符串识别任务的复杂性，因为它在特殊的预处理，分割和一组专门用于特定长度的字符串的分类器中删除了经典步骤。
An end-to-end solution for handwritten numeral string recognition is proposed, in which the numeral string is considered as composed of objects automatically detected and recognized by a YoLo-based model. The main contribution of this paper is to avoid heuristic-based methods for string preprocessing and segmentation, the need for task-oriented classifiers, and also the use of specific constraints related to the string length. A robust experimental protocol based on several numeral string datasets, including one composed of historical documents, has shown that the proposed method is a feasible end-to-end solution for numeral string recognition. Besides, it reduces the complexity of the string recognition task considerably since it drops out classical steps, in special preprocessing, segmentation, and a set of classifiers devoted to strings with a specific length.
