Image Segmentation for Trash Detection Using the YOLOv7 Model

Image segmentation is a fundamental task in computer vision and image processing, with critical applications such as environmental image analysis. Against this backdrop, the widespread success of deep learning (DL) has driven the development of new image segmentation approaches leveraging the YOLOv7 model. This study aims to make a significant contribution to waste management by providing an effective solution for identifying waste areas in images, thereby supporting more efficient environmental restoration efforts. By utilizing the YOLOv7 model and transfer learning techniques, this research seeks to enhance the effectiveness of waste area identification in images, demonstrating its potential to support more efficient and sustainable waste management practices.