4 papers
Beyond Convolution: A Taxonomy of Structured Operators for Learning-Based Image Processing
Simone Cammarasana
The convolution operator is the fundamental building block of modern convolutional neural networks (CNNs), owing to its simplicity, translational equivariance, and efficient implem…
Framework of a multiscale data-driven DT of the musculoskeletal system
Martina Paccini, Simone Cammarasana, Giuseppe Patanè
Musculoskeletal disorders (MSDs) are a leading cause of disability worldwide, requiring advanced diagnostic and therapeutic tools for personalised assessment and treatment. Effecti…
Optimal Weighted Convolution for Classification and Denosing
Simone Cammarasana, Giuseppe Patanè
We introduce a novel weighted convolution operator that enhances traditional convolutional neural networks (CNNs) by integrating a spatial density function into the convolution ope…
Optimal Density Functions for Weighted Convolution in Learning Models
Simone Cammarasana, Giuseppe Patanè
The paper introduces the weighted convolution, a novel approach to the convolution for signals defined on regular grids (e.g., 2D images) through the application of an optimal dens…