以下是一篇关于二维码识别技术的论文，供参考：
题目：基于深度学习的二维码识别技术研究
摘要：二维码作为一种新型的信息编码方式，已经广泛应用于各个领域。然而，传统的二维码识别技术存在着识别速度慢、识别率低等问题。本文提出了一种基于深度学习的二维码识别技术，通过使用卷积神经网络（CNN）对二维码图像进行特征提取和分类，实现了快速、准确的二维码识别。实验结果表明，该方法在识别速度和识别率方面均优于传统的二维码识别技术。
关键词：二维码；深度学习；卷积神经网络；特征提取；分类
Abstract: As a new information coding method, QR code has been widely used in various fields. However, traditional QR code recognition technology has problems such as slow recognition speed and low recognition rate. This paper proposes a QR code recognition technology based on deep learning, which uses convolutional neural network (CNN) to extract features and classify QR code images, achieving fast and accurate QR code recognition. Experimental results show that this method is superior to traditional QR code recognition technology in terms of recognition speed and recognition rate.
Keywords: QR code; deep learning; convolutional neural network; feature extraction; classification
题目：基于深度学习的二维码识别技术研究
摘要：二维码作为一种新型的信息编码方式，已经广泛应用于各个领域。然而，传统的二维码识别技术存在着识别速度慢、识别率低等问题。本文提出了一种基于深度学习的二维码识别技术，通过使用卷积神经网络（CNN）对二维码图像进行特征提取和分类，实现了快速、准确的二维码识别。实验结果表明，该方法在识别速度和识别率方面均优于传统的二维码识别技术。
关键词：二维码；深度学习；卷积神经网络；特征提取；分类
Abstract: As a new information coding method, QR code has been widely used in various fields. However, traditional QR code recognition technology has problems such as slow recognition speed and low recognition rate. This paper proposes a QR code recognition technology based on deep learning, which uses convolutional neural network (CNN) to extract features and classify QR code images, achieving fast and accurate QR code recognition. Experimental results show that this method is superior to traditional QR code recognition technology in terms of recognition speed and recognition rate.
Keywords: QR code; deep learning; convolutional neural network; feature extraction; classification
