most citedI-SPLIT: Deep Network Interpretability for Split Computing

20 citations · 21 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2023

Neuro-symbolic Empowered Denoising Diffusion Probabilistic Models for Real-time Anomaly Detection in Industry 4.0

Luigi Capogrosso, Alessio Mascolini, Federico Girella +10

Industry 4.0 involves the integration of digital technologies, such as IoT, Big Data, and AI, into manufacturing and industrial processes to increase efficiency and productivity. A…

cs.LO2023

HermesBDD: A Multi-Core and Multi-Platform Binary Decision Diagram Package

Luigi Capogrosso, Luca Geretti, Marco Cristani +2

BDDs are representations of a Boolean expression in the form of a directed acyclic graph. BDDs are widely used in several fields, particularly in model checking and hardware verifi…

cs.DC2023★ 1 cited

Split-Et-Impera: A Framework for the Design of Distributed Deep Learning Applications

Luigi Capogrosso, Federico Cunico, Michele Lora +3

Many recent pattern recognition applications rely on complex distributed architectures in which sensing and computational nodes interact together through a communication network. D…

cs.HC2022

Toward Smart Doors: A Position Paper

Luigi Capogrosso, Geri Skenderi, Federico Girella +2

Conventional automatic doors cannot distinguish between people wishing to pass through the door and people passing by the door, so they often open unnecessarily. This leads to the…

cs.CV2022★ 20 cited

I-SPLIT: Deep Network Interpretability for Split Computing

Federico Cunico, Luigi Capogrosso, Francesco Setti +3

This work makes a substantial step in the field of split computing, i.e., how to split a deep neural network to host its early part on an embedded device and the rest on a server.…