Open ainazHjm opened 5 years ago
I trained the FCNwPool model on the new dataset for Veneto (with no-data points) without oversampling but the results are not good. It doesn't seem like a coherent susceptibility map and I don't know the reason why. I'm starting to think that my model might not be a good model to use for this task. I'm going to try this model pixel wise as well. to see how the results change. Results on validation set: Results on train set:
I found a major bug in my data: my slope feature (which is between 0 and 360) has large real values that I thought I was normalizing but I wasn't! So I guess one reason that the model is doing worse than anticipated is this. Rest of my data is categorical that I'm using them as one hot. I processed the dataset again and normalized the slope features. I'm going to retrain the previous model (FCNwPool) on both large images (200x200) and pixel-wise and see how the results change. One good thing about the pixel-wise training is that I can actually oversample the landslide points.