Fig. 6

An illustration of the blind unmixing autoencoder (BAE) method. The autoencoder is trained on an augmented dataset of 19 lakes, with epochs varying based on the objective function and hyperparameter optimization. Post-training, latent layer activations provide abundance estimates, and the first layer decoder weights yield endmember estimates. The abundance estimates of the test set are derived by using only the encoder part and inputting the test dataset. The legend “BG” stands for background.