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CENSUS-HWR: a large training dataset for offline handwriting recognition

2023-05-25 17:31:39
Chetan Joshi, Lawry Sorenson, Ammon Wolfert, Dr. Mark Clement, Dr. Joseph Price, Dr. Kasey Buckles


Progress in Automated Handwriting Recognition has been hampered by the lack of large training datasets. Nearly all research uses a set of small datasets that often cause models to overfit. We present CENSUS-HWR, a new dataset consisting of full English handwritten words in 1,812,014 gray scale images. A total of 1,865,134 handwritten texts from a vocabulary of 10,711 words in the English language are present in this collection. This dataset is intended to serve handwriting models as a benchmark for deep learning algorithms. This huge English handwriting recognition dataset has been extracted from the US 1930 and 1940 censuses taken by approximately 70,000 enumerators each year. The dataset and the trained model with their weights are freely available to download at this https URL.

Abstract (translated)

自动手写识别的进展受到了缺乏大型训练数据的困扰。几乎所有研究都使用了一些小型数据集,这往往导致模型过拟合。我们提出了CENSUS-HWR,这是一个新的数据集,包含1,812,014张灰度图像上的全英语手写单词。这个数据集包含了总共1,865,134篇从英语语言中 vocabulary为10,711个单词的手写文本。这个数据集旨在作为深度学习算法的基准手写模型。这个巨大的英语手写识别数据集是从美国1930和1940年人口普查中每年由大约70,000名调查员收集到的。数据集和训练模型及其权重可以在这个httpsURL上免费下载。



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