Automated Garbage Classification using Deep Learning

To lessen the mounting burden on landfills, recycling household and industrial waste has been suggested as a viable solution. However, effective waste management requires proper segregation of waste types as each category requires different treatment. The current segregation process involves manual sorting which can be time-consuming and Workforce-intensive. In this study, a novel approach using deep learning techniques was utilized to automatically classify waste based on its image into six distinct types: paper, metal, plastic, glass, trash and cardboard. CNN model was employed for the waste classification task.