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Handwriting Recognition
Text Detection
Text Detection
|...
许可协议: CC-BY-SA 4.0

Overview

Overview

This dataset consists of more than four hundred thousand handwritten names collected through charity projects.

Character Recognition utilizes image processing technologies to convert characters on scanned documents into digital forms. It typically performs well in machine-printed fonts. However, it still poses difficult challenges for machines to recognize handwritten characters, because of the huge variation in individual writing styles.

There are 206,799 first names and 207,024 surnames in total. The data was divided into a training set (331,059), testing set (41,382), and validation set (41,382) respectively.

Content

The input data here are hundreds of thousands of images of handwritten names. In the Data, you’ll find the transcribed images broken up into test, training, and validation sets.

Image Lable follow the following naming format enabling you to extend the data set with your own data.

Image URL
D2M 15 0010079F 0002 1 first name.jpg
D2M 15 0010079F 0002 1 surname.jpg
D2M 15 0010079F 0003 2 surname.jpg
D2M 15 0010079F 0004 3 first name.jpg
D2M 15 0010079F 0004 3 surname.jpg
D2M 15 0010079F 0005 4 first name.jpg
D2M 15 0010079F 0006 5 first name.jpg
D2M 15 0010079F 0006 5 surname.jpg
D2M 15 0010079F 0007 6 first name.jpg

Inspiration

The Inspiration of this is to explore the task of classifying handwritten text and to convert handwritten text into the digital format using various approaches out there

数据概要
数据格式
text, image,
数据量
413.704K
文件大小
1290.39GB
发布方
landlord
| 数据量 413.704K | 大小 1290.39GB
Handwriting Recognition
Text Detection
Text Detection
许可协议: CC-BY-SA 4.0

Overview

Overview

This dataset consists of more than four hundred thousand handwritten names collected through charity projects.

Character Recognition utilizes image processing technologies to convert characters on scanned documents into digital forms. It typically performs well in machine-printed fonts. However, it still poses difficult challenges for machines to recognize handwritten characters, because of the huge variation in individual writing styles.

There are 206,799 first names and 207,024 surnames in total. The data was divided into a training set (331,059), testing set (41,382), and validation set (41,382) respectively.

Content

The input data here are hundreds of thousands of images of handwritten names. In the Data, you’ll find the transcribed images broken up into test, training, and validation sets.

Image Lable follow the following naming format enabling you to extend the data set with your own data.

Image URL
D2M 15 0010079F 0002 1 first name.jpg
D2M 15 0010079F 0002 1 surname.jpg
D2M 15 0010079F 0003 2 surname.jpg
D2M 15 0010079F 0004 3 first name.jpg
D2M 15 0010079F 0004 3 surname.jpg
D2M 15 0010079F 0005 4 first name.jpg
D2M 15 0010079F 0006 5 first name.jpg
D2M 15 0010079F 0006 5 surname.jpg
D2M 15 0010079F 0007 6 first name.jpg

Inspiration

The Inspiration of this is to explore the task of classifying handwritten text and to convert handwritten text into the digital format using various approaches out there

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