Source code for replicating experiments in the paper: Książek, K.; Romaszewski, M.; Głomb, P.; Grabowski, B.; Cholewa, M. Blood Stain Classification with Hyperspectral Imaging and Deep Neural Networks. Sensors 2020, 20, 6666. https://doi.org/10.3390/s20226666

The dataset is available online: https://zenodo.org/record/3984905

• Make sure the paths in data_paths.py are correct
• Run main_train.py to train DNN models, run main_test.py to test them
• Run hyperblood_classification_svm.py for reference SVM experiments

All files in this repository except:

• data_dataset.py
• data_loader.py
• main_test.py
• main_train.py
• models.py
• trainer.py
• utils.py

are licenced under GNU GENERAL PUBLIC LICENSE Version 3.

However, the above files are based on the code in library:

https://github.com/nshaud/DeepHyperX

for paper

N. Audebert, B. Le Saux and S. Lefevre, "Deep Learning for Classification of Hyperspectral Data: A Comparative Review," in IEEE Geoscience and Remote Sensing Magazine, vol. 7, no. 2, pp. 159-173, June 2019.

The code is used for RESEARCH AND NON COMMERCIAL PURPOSES under the licence: https://github.com/nshaud/DeepHyperX/blob/master/License