Monte_carlo_dropout

Using monte carlo dropout to have an estimation of predictions uncertainty

instalation

cd monte_carlo_dropout
pip install -e ./

usage

executing the unet_learner function will give you the modified unet with dropout. using the DropOutAlexnet class will give you the alexnet architecture with dropout added.

credits:

Fastai online resources:

• Complete code for image segmentation with the One Hundred Layers Tiramisu (FC-DenseNet model) https://github.com/fastai/course-v3/blob/master/nbs/dl1/lesson3-camvid-tiramisu.ipynb
• Research papers used
  • Dropout as a Bayesian Approximation: Representing Model: https://arxiv.org/abs/1506.02142
  • Bayesian Convolutional Neural Networks with Bernoulli Approximate Variational Inference: https://arxiv.org/abs/1506.02158
  • Nature paper : https://www.nature.com/articles/s41598-019-50587-1?fbclid=IwAR3vS2Jsa16NtOdFgp-I_deIwT8ipsK0isY6oIzBeaPHjOllhDSv1FfAVGg