DOHMO: Embedded Computer Vision in Co-Housing Scenarios. - Geri Skenderi; Alessia Bozzini; Luigi Capogrosso; Enrico Carlo Agrillo; Giovanni Perbellini; Franco Fummi; Marco Cristani (FDL, 2021)

Toward Smart Doors: A Position Paper. - Luigi Capogrosso; Geri Skenderi; Federico Girella; Franco Fummi; Marco Cristani (ICPR Workshops (2), 2022)

I-SPLIT: Deep Network Interpretability for Split Computing. - Federico Cunico; Luigi Capogrosso; Francesco Setti; Damiano Carra; Franco Fummi; Marco Cristani (ICPR, 2022)

The Post-pandemic Effects on IoT for Safety: The Safe Place Project. - Federico Cunico; Luigi Capogrosso; Alberto Castellini; Francesco Setti; Patrik Pluchino; Filippo Zordan; Valeria Santus; Anna Spagnolli; Stefano Cordibella; Giambattista Gennari; Mauro Borgo; Alberto Sozza; et al. (DATE, 2023)

Towards Deep Learning-based Occupancy Detection Via WiFi Sensing in Unconstrained Environments. - Cristian Turetta; Geri Skenderi; Luigi Capogrosso; Florenc Demrozi; Philipp H. Kindt; Alejandro Masrur; Franco Fummi; Marco Cristani; Graziano Pravadelli (DATE, 2023)

Split-Et-Impera: A Framework for the Design of Distributed Deep Learning Applications. - Luigi Capogrosso; Federico Cunico; Michele Lora; Marco Cristani; Franco Fummi; Davide Quaglia (DDECS, 2023)

HermesBDD: A Multi-Core and Multi-Platform Binary Decision Diagram Package. - Luigi Capogrosso; Luca Geretti; Marco Cristani; Franco Fummi; Tiziano Villa (DDECS, 2023)

Neuro-Symbolic Empowered Denoising Diffusion Probabilistic Models for Real-Time Anomaly Detection in Industry 4.0: Wild-and-Crazy-Idea Paper. - Luigi Capogrosso; Alessio Mascolini; Federico Girella; Geri Skenderi; Sebastiano Gaiardelli; Nicola Dall'Ora; Francesco Ponzio; Enrico Fraccaroli; Santa Di Cataldo; Sara Vinco; Enrico Macii; Franco Fummi; et al. (FDL, 2023)

Designing Logic Tensor Networks for Visual Sudoku Puzzle Classification. - Lia Morra; Alberto Azzari; Letizia Bergamasco; Marco Braga; Luigi Capogrosso; Federico Delrio; Giuseppe Di Giacomo; Simone Eiraudo; Giorgia Ghione; Rocco Giudice; Alkis Koudounas; Luca Piano; et al. (NeSy, 2023)

Neuro-symbolic Empowered Denoising Diffusion Probabilistic Models for Real-time Anomaly Detection in Industry 4.0. - Luigi Capogrosso; Alessio Mascolini; Federico Girella; Geri Skenderi; Sebastiano Gaiardelli; Nicola Dall'Ora; Francesco Ponzio; Enrico Fraccaroli; Santa Di Cataldo; Sara Vinco; Enrico Macii; Franco Fummi; et al. (CoRR, 2023)

Disentangled Latent Spaces Facilitate Data-Driven Auxiliary Learning. - Geri Skenderi; Luigi Capogrosso; Andrea Toaiari; Matteo Denitto; Franco Fummi; Simone Melzi; Marco Cristani (CoRR, 2023)

Leveraging Latent Diffusion Models for Training-Free in-Distribution Data Augmentation for Surface Defect Detection. - Federico Girella; Ziyue Liu; Franco Fummi; Francesco Setti; Marco Cristani; Luigi Capogrosso (CBMI, 2024)

MTL-Split: Multi-Task Learning for Edge Devices using Split Computing. - Luigi Capogrosso; Enrico Fraccaroli; Samarjit Chakraborty; Franco Fummi; Marco Cristani (DAC, 2024)

MDiFF: Exploiting Multimodal Score-Based Diffusion Models for New Fashion Product Performance Forecasting. - Andrea Avogaro; Luigi Capogrosso; Franco Fummi; Marco Cristani (ECCV Workshops (1), 2024)

Enhancing Split Computing and Early Exit Applications through Predefined Sparsity. - Luigi Capogrosso; Enrico Fraccaroli; Giulio Petrozziello; Francesco Setti; Samarjit Chakraborty; Franco Fummi; Marco Cristani (FDL, 2024)

Dif4FF: Leveraging Multimodal Diffusion Models and Graph Neural Networks for Accurate New Fashion Product Performance Forecasting. - Andrea Avogaro; Luigi Capogrosso; Franco Fummi; Marco Cristani (ICPR (8), 2024)

SITUATE: Indoor Human Trajectory Prediction Through Geometric Features and Self-supervised Vision Representation. - Luigi Capogrosso; Andrea Toaiari; Andrea Avogaro; Uzair Khan; Aditya Jivoji; Franco Fummi; Marco Cristani (ICPR (16), 2024)

Exploiting Multimodal Latent Diffusion Models for Accurate Anomaly Detection in Industry 5.0. - Luigi Capogrosso; Alvise Vivenza; Andrea Chiarini; Francesco Setti; Marco Cristani (Ital-IA, 2024)

Learning-Enabled CPS for Edge-Cloud Computing. - Luigi Capogrosso; Shengjie Xu; Enrico Fraccaroli; Marco Cristani; Franco Fummi; Samarjit Chakraborty (SIES, 2024)

Diffusion-Based Image Generation for In-Distribution Data Augmentation in Surface Defect Detection. - Luigi Capogrosso; Federico Girella; Francesco Taioli; Michele Dalla Chiara; Muhammad Aqeel; Franco Fummi; Francesco Setti; Marco Cristani (VISIGRAPP (2): VISAPP, 2024)

A Machine Learning-Oriented Survey on Tiny Machine Learning. - Luigi Capogrosso; Federico Cunico; Dong Seon Cheng; Franco Fummi; Marco Cristani (IEEE Access, 2024)

Enhancing Safety and Privacy in Industry 4.0: The ICE Laboratory Case Study. - Federico Cunico; Stefano Aldegheri; Andrea Avogaro; Michele Boldo; Nicola Bombieri; Luigi Capogrosso; Ariel Caputo; Damiano Carra; Stefano Centomo; Dong Seon Cheng; Ettore Cinquetti; Marco Cristani; et al. (IEEE Access, 2024)

Controllers for Edge-Cloud Cyber-Physical Systems. - Tingan Zhu; Prateek Ganguli; Arkaprava Gupta; Shengjie Xu; Luigi Capogrosso; Enrico Fraccaroli; Marco Cristani; Franco Fummi; Samarjit Chakraborty (COMSNETS, 2025)

Human-Centered Digital Twin for Industry 5.0. - Francesco Biondani; Luigi Capogrosso; Nicola Dall'Ora; Enrico Fraccaroli; Marco Cristani; Franco Fummi (DATE, 2025)

LO-SC: Local-Only Split Computing for Accurate Deep Learning on Edge Devices. - Luigi Capogrosso; Enrico Fraccaroli; Marco Cristani; Franco Fummi; Samarjit Chakraborty (VLSID, 2025)

New Fashion Products Performance Forecasting: A Survey on Evolutions, Models and Emerging Trends. - Andrea Avogaro; Luigi Capogrosso; Andrea Toaiari; Franco Fummi; Marco Cristani (CoRR, 2025)

KairosAD: A SAM-Based Model for Industrial Anomaly Detection on Embedded Devices. - Uzair Khan; Franco Fummi; Luigi Capogrosso (CoRR, 2025)