CNN-based plastic waste detection system

Guezouli Larbi, Grourou Aya Aridj, Louchen Saher
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Abstract

Plastic waste has become a pressing global concern in recent decades, posing significant challenges to our environment due to its non-biodegradable nature and causing significant pollution and damage to our planet. Recycling plastic waste is one of the most effective solutions to this dilemma, which is why the aim of our project was to create a system that detects plastic waste using a large dataset with labeled data and one of the most famous deep learning neural networks, “Convolutional Neural Networks,” to classify and speed up the waste collection process and provide an easier recycling process. Thanks to our work, we have achieved 97% accuracy.
基于cnn的塑料垃圾检测系统
近几十年来,塑料垃圾已成为一个紧迫的全球问题,由于其不可生物降解的性质,对我们的环境构成了重大挑战,对我们的地球造成了严重的污染和破坏。回收塑料垃圾是解决这一困境的最有效方法之一,这就是为什么我们项目的目标是创建一个系统,使用带有标记数据的大型数据集和最著名的深度学习神经网络之一“卷积神经网络”来检测塑料垃圾,以分类和加速废物收集过程,并提供更容易的回收过程。由于我们的工作,我们达到了97%的准确率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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