39 citations · 90 across the 12 of their papers we have counts for
5 papers · 1 filter
Q-Segment: Segmenting Images In-Sensor for Vessel-Based Medical Diagnosis
Pietro Bonazzi, Yawei Li, Sizhen Bian +1
This paper addresses the growing interest in deploying deep learning models directly in-sensor. We present "Q-Segment", a quantized real-time segmentation algorithm, and conduct a…
Quantitative Evaluation of a Multi-Modal Camera Setup for Fusing Event Data with RGB Images
Julian Moosmann, Jakub Mandula, Philipp Mayer +2
Event-based cameras, also called silicon retinas, potentially revolutionize computer vision by detecting and reporting significant changes in intensity asynchronous events, offerin…
Ultra-Efficient On-Device Object Detection on AI-Integrated Smart Glasses with TinyissimoYOLO
Julian Moosmann, Pietro Bonazzi, Yawei Li +4
Smart glasses are rapidly gaining advanced functions thanks to cutting-edge computing technologies, especially accelerated hardware architectures, and tiny Artificial Intelligence…
Flexible and Fully Quantized Ultra-Lightweight TinyissimoYOLO for Ultra-Low-Power Edge Systems
Julian Moosmann, Hanna Mueller, Nicky Zimmerman +3
This paper deploys and explores variants of TinyissimoYOLO, a highly flexible and fully quantized ultra-lightweight object detection network designed for edge systems with a power…
TinyissimoYOLO: A Quantized, Low-Memory Footprint, TinyML Object Detection Network for Low Power Microcontrollers
Julian Moosmann, Marco Giordano, Christian Vogt +1
This paper introduces a highly flexible, quantized, memory-efficient, and ultra-lightweight object detection network, called TinyissimoYOLO. It aims to enable object detection on m…