Yearly Archives: 2022

Our New pre-printed: Deep Learning Regression for Quantitative LIBS Analysis of Aluminium Scrap

Our New pre-printed: Deep Learning Regression for Quantitative LIBS Analysis of Aluminium Scrap

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…

Continue Reading Our New pre-printed: Deep Learning Regression for Quantitative LIBS Analysis of Aluminium Scrap
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 :)

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…

Continue Reading 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 :)
Our new article is out: Real-time classification of aluminum metal scrap with laser-induced breakdown spectroscopy using deep and other machine learning approaches.

Our new article is out: Real-time classification of aluminum metal scrap with laser-induced breakdown spectroscopy using deep and other machine learning approaches.

 In this study, the use of Laser-Induced Breakdown Spectroscopy (LIBS), Machine Learning (ML), and Deep Learning (DL) for the three-way sorting of Aluminum (Al) is proposed. Two sample sets of…

Continue Reading Our new article is out: Real-time classification of aluminum metal scrap with laser-induced breakdown spectroscopy using deep and other machine learning approaches.
Assessing the efficiency of Laser-Induced Breakdown Spectroscopy (LIBS) based sorting of post-consumer aluminium​ scrap !!

Assessing the efficiency of Laser-Induced Breakdown Spectroscopy (LIBS) based sorting of post-consumer aluminium​ scrap !!

The life cycle engineering (LCE) research group (SIM² – KU Leuven) of the KU Leuven has demonstrated the capability of LIBS in combination with machine learning techniques to sort aluminium post-consumer scrap…

Continue Reading Assessing the efficiency of Laser-Induced Breakdown Spectroscopy (LIBS) based sorting of post-consumer aluminium​ scrap !!
Simultaneous Mass Estimation and Class Classification of Scrap Metals using Deep Learning

Simultaneous Mass Estimation and Class Classification of Scrap Metals using Deep Learning

The KU Leuven's lifecycle engineering (LCE) research group (SIM² - KU Leuven) and EAVISE Research Group have explored a new methodology for mass estimation and classification of scrap metals using…

Continue Reading Simultaneous Mass Estimation and Class Classification of Scrap Metals using Deep Learning