Handwritten Character Recognition Using Deep-Learning

被引：0

作者：

Vaidya, Rohan ^{[1
]}

Trivedi, Darshan ^{[1
]}

Satra, Sagar ^{[1
]}

Pimpale, Mrunalini ^{[1
]}

机构：

[1] Dwarkadas J Sanghvi Coll Engn, EXTC Dept, Mumbai, India

来源：

PROCEEDINGS OF THE 2018 SECOND INTERNATIONAL CONFERENCE ON INVENTIVE COMMUNICATION AND COMPUTATIONAL TECHNOLOGIES (ICICCT) | 2018年

关键词：

Neural Networks; Deep Learning; Tensorflow; !text type='Python']Python[!/text; OpenCV; Android; !text type='JAVA']JAVA[!/text;

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

In this paper we present an innovative method for offline handwritten character detection using deep neural networks. In today world it has become easier to train deep neural networks because of availability of huge amount of data and various Algorithmic innovations which are taking place. Now-a-days the amount of computational power needed to train a neural network has increased due to the availability of GPU's and other cloud based services like Google Cloud platform and Amazon Web Services which provide resources to train a Neural network on the cloud. We have designed a image segmentation based Handwritten character recognition system. In our system we have made use of OpenCV for performing Image processing and have used Tensorflow for training a the neural Network. We have developed this system using python programming language.

引用

页码：772 / 775

页数：4

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