基于卷积神经网络的垃圾分类系统的实现

Implementation of garbage classification system based onconvolution neural network

针对当前生活垃圾人工分类效率低、效果欠佳等问题,提出了基于卷积神经网络算法的智能垃圾分类系统。通过对硬件、通信、软件等模块的设计,实现了系统的垃圾识别、垃圾分类、分类结果反馈等功能。测试表明,该系统针对日常生活垃圾的平均识别率超过93%。其以较低的成本、可持续迭代更新的垃圾识别率为当下社会垃圾分类提供了高效的解决方案。

Aiming at the problems of low efficiency and poor effect of domestic waste manual classification,an intelligent garbage classification system based on convolution neural network algorithm is proposed.Through the design of hardware,communication and software modules,the functions of garbage identification,garbage classification and classification result feedback are realized.The test results show that the average recognition rate of the system is over 93%.It provides an efficient solution to the current social garbage classification with low cost and sustainable iterative update rate.