Solid waste classification using deep neural network: A transfer learning approach

This study develops an accurate and efficient model for automatically classifying various types of solid waste, using a large, annotated dataset of waste objects from diverse sources and applying state-of-theart deep learning techniques, including advanced architectures such as Xception, DenseNet, and EfficientNet.