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Research on the algorithm of urban waste classification and recycling based on deep learning technology

机译：基于深度学习技术的城市废物分类与回收算法研究

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In view of the rapid growth of municipal solid waste (MSW), a large number of MSW are transported to the outside of the city for landfill or incineration, only part of the MSW is treated innocuously, the speed of MSW treatment is slow, and the level of garbage classification intelligence is low, this paper proposes an algorithm of MSW classification and recycling based on deep learning technology, and uses convolution neural network to build garbage intelligence simultaneous interpreting and classification algorithm, which improves the accuracy and speed of garbage image recognition. The algorithm is compared with the traditional BP neural network algorithm. The simulation results show that the algorithm is 30% faster than the traditional algorithm. The classification algorithm has faster response speed, higher accuracy and stronger robustness.
机译：鉴于市政固体废物（MSW）的快速增长，大量的MSW被运送到城市外部进行垃圾填埋场或焚烧，只有一部分的MSW被无害地治疗，MSW治疗的速度很慢，而且本文提出了一种基于深度学习技术的MSW分类和回收算法，采用卷积神经网络构建垃圾智能同声解释和分类算法，这提高了垃圾图像识别的准确性和速度。将算法与传统的BP神经网络算法进行比较。仿真结果表明，算法比传统算法快30％。分类算法具有更快的响应速度，更高的精度和更强的鲁棒性。

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