activity
20232026
most citedEnhancing Neural Architecture Search with Multiple Hardware Constraints for Deep Learning Model Deployment on Tiny IoT Devices

24 citations · 29 across the 9 of their papers we have counts for

collaborators

10 papers

cs.DL2026

GitScholar: A Dataset for Predicting AI Research Impact from GitHub Engagement

Emilien Guandalino, Lorenz K. Müller, Beatrice Alessandra Motetti +2

With the rapid pace of AI research and the hundreds of daily new publications, staying up-to-date with the latest developments has become increasingly difficult. For researchers, q…

cs.AI2026

Wyvern: An Agentic Framework for Generating Grounded Multimodal Reports

Beatrice Alessandra Motetti, Emilien Guandalino, Daniele Jahier Pagliari +4

In the current artificial intelligence-driven innovation era, the pace of knowledge growth is accelerating, and is hard to keep up with. While generative models are increasingly us…

cs.LG2026

MAUPITI: On-Device Prototype-Based Learning on a Smart Infrared Sensor

Beatrice Alessandra Motetti, Tanguy Dugas du Villard, Matteo Risso +7

Low-resolution infrared (IR) array sensors represent an interesting solution for privacy-preserving human sensing in embedded systems. In this letter, we describe a smart multi-pix…

cs.CV2026

BlankSkip: Early-exit Object Detection onboard Nano-drones

Carlo Marra, Beatrice Alessandra Motetti, Alessio Burrello +3

Deploying tiny computer vision Deep Neural Networks (DNNs) on-board nano-sized drones is key for achieving autonomy, but is complicated by the extremely tight constraints of their…

cs.CV2024★ 1 cited

Building Damage Assessment in Conflict Zones: A Deep Learning Approach Using Geospatial Sub-Meter Resolution Data

Matteo Risso, Alessia Goffi, Beatrice Alessandra Motetti +6

Very High Resolution (VHR) geospatial image analysis is crucial for humanitarian assistance in both natural and anthropogenic crises, as it allows to rapidly identify the most crit…

cs.LG2024

Joint Pruning and Channel-wise Mixed-Precision Quantization for Efficient Deep Neural Networks

Beatrice Alessandra Motetti, Matteo Risso, Alessio Burrello +3

The resource requirements of deep neural networks (DNNs) pose significant challenges to their deployment on edge devices. Common approaches to address this issue are pruning and mi…