2 citations · 2 across the 2 of their papers we have counts for
3 papers
Moving Frame Net: SE(3)-Equivariant Network for Volumes
Mateus Sangalli, Samy Blusseau, Santiago Velasco-Forero +1
Equivariance of neural networks to transformations helps to improve their performance and reduce generalization error in computer vision tasks, as they apply to datasets presenting…
Scale Equivariant U-Net
Mateus Sangalli, Samy Blusseau, Santiago Velasco-Forero +1
In neural networks, the property of being equivariant to transformations improves generalization when the corresponding symmetry is present in the data. In particular, scale-equiva…
Scale Equivariant Neural Networks with Morphological Scale-Spaces
Mateus Sangalli, Samy Blusseau, Santiago Velasco-Forero +1
The translation equivariance of convolutions can make convolutional neural networks translation equivariant or invariant. Equivariance to other transformations (e.g. rotations, aff…