A set of benchmarks for Handwritten Text Recognition on historical documents

作者：

Highlights：

• Handwritten Text Recognition is researched in this paper with a set of free available benchmarks.

• Freely available tools are provided for Handwritten Text Recognition.

• Competitive results are provided with Convolutional Recurrent Neural Networks and N-gram language models.

• New challenges are described related to Handwritten Text Recognition.

摘要

•Handwritten Text Recognition is researched in this paper with a set of free available benchmarks.•Freely available tools are provided for Handwritten Text Recognition.•Competitive results are provided with Convolutional Recurrent Neural Networks and N-gram language models.•New challenges are described related to Handwritten Text Recognition.

论文关键词：Historical handwritten text recognition,Hidden Markov models,Convolutional neural networks,Recurrent neural networks,Language modeling

论文评审过程：Received 31 July 2018, Revised 5 May 2019, Accepted 14 May 2019, Available online 16 May 2019, Version of Record 27 May 2019.

论文官网地址：https://doi.org/10.1016/j.patcog.2019.05.025