Managing Household Waste through Transfer Learning

arXiv:2402.09437v1 Announce Type: new
Abstract: As the world continues to face the challenges of climate change, it is crucial to consider the environmental impact of the technologies we use. In this study, we investigate the performance and computational carbon emissions of various transfer learning models for garbage classification. We examine the MobileNet, ResNet50, ResNet101, and EfficientNetV2S and EfficientNetV2M models. Our findings indicate that the EfficientNetV2 family achieves the highest accuracy, recall, f1-score, and IoU values. However, the EfficientNetV2M model requires …

abstract arxiv carbon challenges change classification climate climate change computational cs.cv emissions environmental environmental impact face impact mobilenet performance resnet50 study technologies through transfer transfer learning type waste world