基于深度学习的手写体数字识别技术研究

摘要：本文主要探讨了深度学习方法在手写数字识别中的应用，并针对其存在的问题提出了应对策略。首先介绍了相关技术，包括数字图像处理技术、模式识别技术和深度学习技术，并对手写数字图像处理技术进行了研究。然后详细讲解了深度学习在手写数字识别中的应用，包括基本原理、常见深度学习模型介绍和基于深度学习的手写数字识别模型构建。接着讨论了深度学习方法在手写数字识别中存在的问题，包括数据量不足问题、过拟合问题和硬件设备需求问题，并提出了应对策略，包括数据增强、正则化和模型压缩。总之，本文对深度学习方法在手写数字识别中应用的现状及问题进行了探讨，提出了一定的应对策略，具有一定的理论和应用价值。

关键词：手写数字识别、深度学习、数据增强、正则化、模型压缩

Abstract:This paper mainly discusses the application of deep learning in handwritten digit recognition, and puts forward some countermeasures for the existing problems. Firstly, related technologies, including digital image processing technology, pattern recognition technology and deep learning technology, are introduced, and hand-written digital image processing technology is studied. Then it explains the application of deep learning in handwritten digit recognition in detail, including the basic principle, the introduction of common deep learning models and the construction of handwritten digit recognition models based on deep learning. Then it discusses the problems of deep learning in handwritten digit recognition, including insufficient data, overfitting and hardware requirements, and puts forward some countermeasures, including data enhancement, regularization and model compression. In short, this paper discusses the current situation and problems of the application of deep learning in handwritten digit recognition, and puts forward some coping strategies, which has certain theoretical and application value.

Key words：Handwritten digit recognition, deep learning, data enhancement, regularization, model compression

题目：基于深度学习的手写体数字识别技术研究 1

摘要： 1

1 绪论 2

1.1研究背景和意义 2

1.2国内外研究现状和进展 2

1.3研究方法和内容 2

2.相关技术介绍 2

2.1数字图像处理技术 2

2.2模式识别技术 3

2.3 深度学习技术 3

3.手写数字图像处理技术研究 4