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Transformation Invariant Cancerous Tissue Classification Using Spatially Transformed DenseNet
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.
Transformation Invariant Cancerous Tissue Classification Using Spatially Transformed DenseNet
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.
Transformation Invariant Cancerous Tissue Classification Using Spatially Transformed DenseNet
Mahdi, Omar (Autor:in) / Nassif, Ali Bou (Autor:in)
21.02.2022
1498061 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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