arXiv:2606. 14824v1 Announce Type: cross Abstract: This document proposes a novel approach to hardware-aware neural architecture search (HW NAS) that considers the resources available on the computing platform running it, enabling its execution on various embedded devices.
By Andrea Mattia Garavagno, Edoardo Ragusa, Paolo Gastaldo, Antonio Frisoli
arXiv:2608. 06252v1 Announce Type: cross Abstract: Deaf and hard-of-hearing people in Bangladesh communicate mainly through Bangla Sign Language (BdSL).
By Saad Ahmed, Md Khalid Syfullaha
The paper presents a rapid pipeline for training and deploying machine‑learning models on the WeBe Band, a wrist‑worn wearable device. It automates the creation of hardware‑efficient models, integrates with the Piccolo AI ecosystem, and supports OTA deployment while profiling latency and memory usage. Experimental results show trade‑offs between classical models and lightweight neural networks for real‑time performance on a microcontroller.
By Ehsan Kourkchi, Asmita Asmita, Houman Homayoun, Mahdi Eslamimehr
arXiv:2607. 22779v1 Announce Type: cross Abstract: Hand gesture recognition via surface electromyography (sEMG) is fundamental to prosthetic control.
By Federico Del Pup, Elisa Tentori, Manfredo Atzori
arXiv:2505. 23939v2 Announce Type: replace Abstract: This paper presents an automatic method for the design of Neural Networks (NNs) at the edge, enabling Machine Learning (ML) access even in privacy-sensitive Internet of Things (IoT) applications.
By Andrea Mattia Garavagno, Edoardo Ragusa, Antonio Frisoli, Paolo Gastaldo
arXiv:2607. 18287v1 Announce Type: cross Abstract: This paper introduces BearingNAS, a Hardware-Aware Neural Architecture Search (HW-NAS) framework designed to shift the intelligence directly onto the sensor die via in-sensor processing.
By Andrea Mattia Garavagno, Edoardo Ragusa, Paolo Gastaldo, Antonio Frisoli, Rodolfo Zunino