摘要
电子垃圾不仅含有多种有毒有害物质,还会造成巨大的资源浪费。研究一种基于图像处理的电子垃圾自动分拣系统,该系统可基于照片识别和分类废弃电器和电子设备,有效回收电子垃圾,有利于节约资源并保护环境。提出了一种使用神经网络进行图像分析的新分类和识别方法,即采用深度学习卷积神经网络对电子垃圾进行分类。实验表明该系统对电子垃圾的识别和分类准确率在89%~96%。
Electronic waste not only contains a variety of toxic and harmful substances,but also causes a huge waste of resources.This paper aims to study an electronic waste classification system based on image processing,which can be used to identify and classify waste electrical and electronic equipment according to information from photos,thus helping in recycling e-waste more effectively,and saving resources and protecting environment.It is proposed and adopted to the system a new classification and recognition method using neural network for image analysis,i.e.,deep learning convolution neural network.The experiment shows that the recognition and classification accuracy of the system is 89%~96%.
作者
钟晓英
ZHONG Xiaoying(Huizhou Technician Institute,Huizhou 516023,China)
出处
《电工技术》
2023年第18期10-12,共3页
Electric Engineering
关键词
图像处理
自动分拣
CNN
深度学习
image processing
automatic sorting
CNN
deep learning
