Update README.md

README.md

@@ -4,10 +4,10 @@ library_name: keras
 
 ## Model description
 
-Autoencoder model trained to compress information from sentinel-2 satellite images using Resnet50 V2 as decoder backbone to extract features. 
+Autoencoder model trained to compress information from sentinel-2 satellite images using Resnet50 V2 as encoder backbone to extract features. 
 The latent space of the model is given by 1024 neurons which can be used to generate embeddings from the sentinel-2 satellite images.
 
-The model was trained using bands 2, 3 and 4 of the Sentinel-2 satellites and for the full Colombia dataset. 
+The model was trained using bands RGB (2, 3 and 4) (Red, Green and Blue) of the Sentinel-2 satellites and using 81 municipalities of Colombia with most dengue cases. 
 
 The input shape of the model is 224, 224, 3. To extract features you should remove the last layer.
 
@@ -17,8 +17,9 @@ The model was trained with images of 81 different cities in Colombia, however it
 
 ## Training and evaluation data
 
-The model was trained with satellite images of 81 different cities in Colombia extracted from sentinel-2.
+The model was trained with satellite images of 81 different cities in Colombia extracted from sentinel-2 using RGB bands using an asymmetric autoencoder. Images with information that could result in noise such as black images were filtered prior to training to avoid noise in the data.
 
+The dataset was split into train and test using 80% for train and 20% to test.
 ## Training procedure
 
 ### Training hyperparameters