Results from deep learning tests using balanced databases for the classification of paper and cardboard materials.
datasetposted on 14.10.2019, 13:28 authored by Carlos Vrancken, Stuart WaglandStuart Wagland, Philip LonghurstPhilip Longhurst
For methodology used to obtain these results please refer to the publication: "Deep learning in material recovery: Development of method to create training database".
These results were obtained using grayscale version of the images.
The "Balanced dataset - classification results" spreadsheet includes:
Sheet 1 - classification results when classifying 3 classes of fibre materials using increasing number of samples per class in a balanced training dataset
Sheet 2 - classification results when using a balanced dataset with 5,000 training samples per class to classify 10 classes of fibre waste material