Smart-Recycling-Deep-Learning

In this project, we developed a "Smart Recycling" system employing Deep Learning techniques. We utilized Data Augmentation and Convolutional Neural Networks (CNN). We rigorously evaluated the model's performance, including classification accuracy on test data, to identify its strengths and weaknesses. Additionally, we enhanced the model's generalizability across different domains by incorporating the ResNet50 architecture.