Results from deep learning tests using balanced databases for the classification of paper and cardboard materials.

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