Integrating multi-sensor systems to sort and monitor complex waste streams is one of the most recent innovations in the recycling industry. The complementary strengths of Laser-Induced Breakdown Spectroscopy (LIBS) and computer vision systems offer a novel multi-sensor solution for the complex task of sorting aluminum (Al) post-consumer scrap into alloy groups. This study presents two novel methods for fusing RGB and Depth images with LIBS using Deep Learning models.
![Our New article is out, and you can read it in the following link for the first 50 days “Classification of aluminum scrap by laser-induced breakdown spectroscopy (LIBS) and RGB + D image fusion using deep learning approaches.”](https://www.ausomproject.eu/wp-content/uploads/2023/01/multiple-output-dl.png)