Paper ID: 2204.11066

Transformation Invariant Cancerous Tissue Classification Using Spatially Transformed DenseNet

Omar Mahdi, Ali Bou Nassif

In this work, we introduce a spatially transformed DenseNet architecture for transformation invariant classification of cancer tissue. Our architecture increases the accuracy of the base DenseNet architecture while adding the ability to operate in a transformation invariant way while simultaneously being simpler than other models that try to provide some form of invariance.

Submitted: Apr 23, 2022