基于深度学习的可回收垃圾自动分拣系统

打开文本图片集

[摘    要]目前，市场对垃圾后端处理仍处于萌芽状态，而深度学习技术作为近些年的热点，能够配合硬件系统，完成可回收垃圾的分拣工作。系统根据视觉识别结果控制相应的机械爪对目标垃圾进行抓取，最终在传送带末端打包。实验结果表明，所提出的方法可以较好地实现预期分拣目标。

[关键词]垃圾分类;深度学习;卷积神经;视觉系统

[中图分类号]TP18 [文献标志码]A [文章编号]2095–6487（2022）08–0–03

Automatic Sorting System for Recyclable Garbage Based on Deep Learning

Xu Li，Liu Yi-zhi，Wang Ze-long，Guo Jin-shuai，Ding Jia-qi

[Abstract]At present， the market for waste back-end treatment is still in its infancy. As a hot spot in recent years， deep learning technology can cooperate with hardware systems to complete the sorting of recyclable garbage. According to the visual recognition result， the system controls the corresponding mechanical claw to grab the target garbage， and finally pack it at the end of the conveyor belt. The experimental results show that the proposed method can achieve the expected sorting goal well.

[Keywords]garbage classification; deep learning; convolutional neural; visual system

1 研制背景及意義

垃圾围城是我国当前城市管理的一大难题，仅2020年新增可回收垃圾总量便超过30亿t。（剩余4166字）

网站仅支持在线阅读（不支持PDF下载），如需保存文章，可以选择【打印】保存。