E Waste

E-waste management is a critical global challenge demanding efficient recycling solutions. Current research focuses on applying advanced computer vision techniques, particularly deep learning models like YOLO and various U-Net architectures, along with hyperspectral imaging, to automate the identification and sorting of electronic components for improved material recovery. These methods leverage both spectral and spatial information from images to classify different e-waste materials with high accuracy, improving the efficiency and effectiveness of recycling processes. The development of large, publicly available datasets and benchmark models is crucial for advancing this field and facilitating broader adoption of these technologies.