The rapid advancement of deep learning technology has led to the presentation of various
network architectures for classification, making it easier to implement intelligent waste …

With the rapid development of deep learning technology, a variety of network models for
classification have been proposed, which is beneficial to the realization of intelligent waste …

The accumulation of solid waste in the urban area is becoming a great concern, and it would
result in environmental pollution and may be hazardous to human health if it is not properly …

The rapid economic and social development has led to a rapid increase in the output of
domestic waste. How to realize waste classification through intelligent methods has become …

In this paper, ConvNeXt is selected as a model for waste classification from digital images.
ConvNeXt is a CNN-based backbone network that has been proposed to further improve the …

This study aims to improve the accuracy of waste sorting through deep learning and to
provide a possibility for intelligent waste classification based on computer vision/mobile …

Nowadays, society is growing and crowded, the construction of automatic smart waste sorter
machine utilizing the intelligent sensors is important and necessary. To build this system …

As people have become more aware of their actions and how they affect their surroundings,
they have realized the dire state of the environment. As a result, the recycling movement has …

The management of solid waste in large urban environments has become a complex
problem due to increasing amount of waste generated every day by citizens and companies …

An automatic classification robot based on effective image recognition could help reduce
huge labors of recycling tasks. Convolutional neural network (CNN) model, such as …