Automatic Sorting of mixed scrap Metals
Our project is concluded, but we are always open to collaboration !!
10/01/2020 – 31/12/2022tin
We are proud to announce the first release of our AUSOM website. We’re very anxious to your reaction. If you have any comments or questions concerning the website or the AUSOM project, please contact us.
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.”
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 […]
This study presents two novel methods for fusing RGB and Depth images with LIBS using Deep Learning models. The first method is a single-output model that combines LIBS UNET and two DenseNets in a late fusion framework. The second method is a multiple-output model that uses the structure of the single-output model to enhance learning […]
Our new pre-printed paper, “Classification of Aluminum Scrap by Laser Induced Breakdown Spectroscopy (LIBS) and RGB+D Image Fusion Using Deep Learning Approaches” is out 🙂
We are focusing to show how #rgb + #3d and #libs systems can be fused to improve the classification of scrap #aluminium. This presents a new multi inputs and outputs #deeplearning structure that encompasses the excellent potential for sorting #postconsumer aluminum scrap. http://ssrn.com/abstract=4272447