Rapid classification of copper concentrate by portable laser-induced breakdown spectroscopy combined with transfer learning and deep convolutional neural network

This paper investigates the combination of laser-induced breakdown spectroscopy 〔LIBS〕 and deep convolutional neural networks 〔CNNs〕 to classify copper concentrate samples using pretrained CNN models through transfer learning. Four pretrained CNN models were compared. The LIBS profiles were augmented into 2D matrices. Three transfer learning methods were tried. All the models got a high classification accuracy of >92%, with the highest at 96.2% for VGG16. These results suggested that the know...