Fuzail Palnak

try changing the dilation rate parameter to Dilation-RF or Dilation-bigger (check the paper for more detail on the dilation rate setting) and again if still the issue exists try using...

Information on which model are you interested in out of the two? 1. [RefineNet trained on INRIA](https://github.com/fuzailpalnak/building-footprint-segmentation/releases/download/alpha/refine.zip) 2. [DlinkNet trained on Massachusetts Buildings Dataset](https://github.com/fuzailpalnak/building-footprint-segmentation/releases/download/alpha/DlinkNet.zip)

### **RefineNet** 1. **Training** - Training was carried out on 384x384 images for around 120 to 130 epochs(I can't remember the exact number) - For Augmentation, I used combination of...

Yes, its the best model. It could be because I also used test time augmentation while inference

@teresalisanti are you running the refine-net model on a custom aerial imagery data ? or Inria data ? And the results are they from finetuned refine-net model ? or just...

unfortunately, I don't have the script that I used for training, it was in my old laptop which I no longer have and top of that, I did not commit...

I used ImageNet weights to initialise ResNet module and used default pytorch initialisation for rest, thats how I setup the training. In the library its default to use ImageNet weights...

One common reason for this is, when augmentation is applied the model gets some hard examples to learn from which causes the validation metric to be lower than training metric,...

If the validation metric is lower than training metric for initial epochs then thats not a problem, however, if the train metric is always higher than validation throughout the training...