Deep Learning Approach to Recyclable Products Classification: Towards Sustainable Waste Management

Effective waste management and recycling are essential for sustainable development environmental conservation. It is a global issue around the globe emerging in Saudi Arabia. The traditional approach to sorting relies on manual labor, which both time-consuming, inefficient, prone errors. Nonetheless, rapid advancement of computer vision techniques has paved way automating garbage classification, resulting enhanced efficiency, feasibility, management. In this regard, study, comprehensive investigation classification using state-of-the-art algorithm, such as Convolutional Neural Network (CNN), well pre-trained models DenseNet169, MobileNetV2, ResNet50V2 been presented. As an outcome CNN model achieved accuracy 88.52%, while ResNet50V2, 94.40%, 97.60%, 98.95% accuracies, respectively. That considerable contrast studies literature. proposed study potential contribution facilitating effective system more greener future. Consequently, it may alleviate burden reduce human error, encourage practices, ultimately promoting