摘要
随着数字化时代的到来,图像识别技术快速发展,社会对图像识别技术的需求量也越来越大。文章对基于深度学习的图像识别技术进行了探讨分析,说明该技术利用深层神经网络模拟人脑的学习过程,自动学习并提取图像中的各种特征表示,从而提高图像识别的准确性,为今后更好地完善图像识别技术提供参考。
With the advent of the digital era,image recognition technology has developed rapidly,and the demand for such technology in society has also been increasing.The article discusses and analyzes image recognition technology based on deep learning,explaining that this technology utilizes deep neural networks to simulate the learning process of the human brain,automatically learns and extracts various feature representations from images,thereby improving the accuracy of image recognition for the purpose of further improving image recognition technology in the future.
作者
李平
LI Ping(Nanfang College·Guangzhou,Guangzhou Guangdong 510970,China)
出处
《信息与电脑》
2025年第20期60-62,共3页
Information & Computer
关键词
深度学习
图像识别
卷积神经网络
应用
deep learning
image recognition
convolutional neural network
application
