19 citations · 31 across the 3 of their papers we have counts for
3 papers
A Continuous Convolutional Trainable Filter for Modelling Unstructured Data
Dario Coscia, Laura Meneghetti, Nicola Demo +2
Convolutional Neural Network (CNN) is one of the most important architectures in deep learning. The fundamental building block of a CNN is a trainable filter, represented as a disc…
A Proper Orthogonal Decomposition approach for parameters reduction of Single Shot Detector networks
Laura Meneghetti, Nicola Demo, Gianluigi Rozza
As a major breakthrough in artificial intelligence and deep learning, Convolutional Neural Networks have achieved an impressive success in solving many problems in several fields i…
A Dimensionality Reduction Approach for Convolutional Neural Networks
Laura Meneghetti, Nicola Demo, Gianluigi Rozza
The focus of this paper is the application of classical model order reduction techniques, such as Active Subspaces and Proper Orthogonal Decomposition, to Deep Neural Networks. We…