A Reliable and Robust Deep Learning Model for Effective Recyclable Waste Classification

In response to the growing waste problem caused by industrialization and modernization, the need for an automated waste sorting and recycling system for sustainable waste management has become ever more pressing. Deep learning has made significant advancements in image classification, making it ideally suited for waste sorting applications. This application depends on the development of a suitable deep learning model capable of accurately categorizing various categories of waste. In this study, we present RWC-Net (recyclable waste classification network), a novel deep learning model designed for the classification of six distinct waste categories using the TrashNet dataset of 2,527 images of waste. The performance of our model is subjected to intensive quantitative and qualitative evaluations and is compared to various state-of-art…