The Image Classification Algorithm Was Implemented on The MNIST Data Set

Wayuan Xiao
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Abstract

In the current era of rapid development of science and technology, the recognition and classification of digital images is the key to solving many problems, such as the application of license plate recognition, document digitization, and remote sensing image surface classification. Based on the MNIST handwritten numerical data set collected by the National Institute of Standards and Technology (NIST), this report uses Python language and PyTorch programming framework to construct a convolutional neural network (CNN) structure and practice and experience the image classification of handwritten digits in the MNIST data set.
在 MNIST 数据集上实施图像分类算法
在科学技术飞速发展的今天,数字图像的识别与分类是解决车牌识别、文档数字化、遥感图像表面分类等诸多问题的关键。本报告基于美国国家标准与技术研究院(NIST)收集的 MNIST 手写数字数据集,使用 Python 语言和 PyTorch 编程框架构建了卷积神经网络(CNN)结构,并对 MNIST 数据集中的手写数字进行了图像分类实践和体验。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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