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