论文标题
使用卷积神经网络的废物分离方法
A Method for Waste Segregation using Convolutional Neural Networks
论文作者
论文摘要
垃圾的隔离是世界上许多国家的主要关注点。即使我们处于现代时代，许多人仍然不知道如何区分有机和可回收废物。正是因此，世界正面临着废物处理的重大危机。在本文中，我们尝试使用深度学习算法来帮助解决这一废物分类问题。废物分为两类，例如有机和可回收。我们提出的模型的准确度为94.9％。尽管其他两个模型也显示出令人鼓舞的结果，但提出的模型的精度最高。借助深度学习，最终可以消除有效废物管理的最大障碍之一。
Segregation of garbage is a primary concern in many nations across the world. Even though we are in the modern era, many people still do not know how to distinguish between organic and recyclable waste. It is because of this that the world is facing a major crisis of waste disposal. In this paper, we try to use deep learning algorithms to help solve this problem of waste classification. The waste is classified into two categories like organic and recyclable. Our proposed model achieves an accuracy of 94.9%. Although the other two models also show promising results, the Proposed Model stands out with the greatest accuracy. With the help of deep learning, one of the greatest obstacles to efficient waste management can finally be removed.
