3 papers
eess.SP2021
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…
math.ST2019
Max-plus Operators Applied to Filter Selection and Model Pruning in Neural Networks
Yunxiang Zhang, Samy Blusseau, Santiago Velasco-Forero +2
Following recent advances in morphological neural networks, we propose to study in more depth how Max-plus operators can be exploited to define morphological units and how they beh…
cs.CV2019
Part-based approximations for morphological operators using asymmetric auto-encoders
Bastien Ponchon, Santiago Velasco-Forero, Samy Blusseau +2
This paper addresses the issue of building a part-based representation of a dataset of images. More precisely, we look for a non-negative, sparse decomposition of the images on a r…