Deep Learning Approaches for Waste Classification

Waste management is a global problem that requires different solutions from country to country as there is no standardized approach. However, efficient waste recycling offers significant opportunities for government revenue generation. Accordingly, our research proposes an automated technology that can accurately detect and sort waste. Recognizing the key role of waste sorting in cost-effective recycling, the goal of our research was to identify and sort individual waste items shown in photographs. Using deep learning techniques, including convolutional neural networks such as ResNet, MobileNetV2 and DenseNet, our goal is to optimize waste management processes.