OCR图像数据集，可用于OCR系统分类算法的基准测试
Scene：
NLPData Type：
Classification
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University of California, Irvine
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Data Set Information:
Data Type: GrayScale Image
The image dataset can be used to benchmark classification algorithm for OCR systems. The highest accuracy obtained in the Test set is 98.47%. Model Description is available in the paper [Web link]
More information on the dataset at [Web link].
Attribute Information:
Image Format: .png
Resolution: 32 by 32
Actual character is centered within 28 by 28 pixel, padding of 2 pixel is added on all four sides of actual character.
Relevant Papers:
S. Acharya, A.K. Pant and P.K. Gyawali a€?Deep Learning based Large Scale Handwritten Devanagari Character Recognitiona€?,In Proceedings of the 9th International Conference on Software, Knowledge, Information Management and Applications (SKIMA), pp. 121-126, 2015.
Citation Request:
The material maybe used for free with the following paper cited,
S. Acharya, A.K. Pant and P.K. Gyawali a€?Deep Learning based Large Scale Handwritten Devanagari Character Recognitiona€?,In Proceedings of the 9th International Conference on Software, Knowledge, Information Management and Applications (SKIMA), pp. 121-126, 2015.
The dataset was created by extraction and manual annotation of thousands of characters from handwritten documents.
Creator Name: Shailesh Acharya, Email: sailes437 '@' gmail.com, Institution: University of North Texas, Cell: +19402200157
Creator Name: Prashnna Kumar Gyawali, Email: gyawali.prasanna '@' gmail.com, Institution: Rochester Institute of Technology
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