Hello all,
I have a couple of questions regarding Esri Deep-learning apps.
1) Freeze - unfreeze backbone:
I would be interested to know which layers of the backbone are frozen by default. Additionally it would be interesting to know which layers are unfrozen when calling "model.unfreeze()". I could not find any details in the documentation.
As a concrete example:
MaskRCNN with ResNet 18 as backbone
"model = MaskRCNN(data, backbone="resnet18", early_stopping=True)"
2) Transfer learning:
I assume that transfer learning is applied by default. Is it possible to use no pre-trained weights and to train the net completely new?
As a concrete example:
MaskRCNN with ResNet 18 as backbone
"model = MaskRCNN(data, backbone="resnet18", early_stopping=True)"
3) Weight initialization schemes:
There are no Informations regarding this parameter "arcgis.env.type_init_tail_parameters". I would be particularly interested in the following: let's assume i use a tiff with 20 channels. I would now like to use a single Band for training. Which weights are used now, R,G or B? Presumably this parameter only applies if there are more than 3 channels in a training?
Thanks!1