39 citations · 90 across the 12 of their papers we have counts for
6 papers · 1 filter
SkyEV: RGB-Event UAV detection and tracking dataset and baseline
Jakub Mandula, Sebastian Heusinger, Julian Moosmann +2
Detecting UAVs in air spaces has become increasingly important due to UAVs widespread availability and easy usage. However, due to their small size, they are typically difficult to…
OpenGlass: Ultra-Low-Power On-Device AI Eyewear with Event-based Vision
Pietro Bonazzi, Julian Moosmann, Ahmet Celik +2
Smart eyewear enables unobtrusive, context-aware interaction through multimodal sensors and on-device intelligence, but is severely limited by power, memory, and compute constraint…
DSORT-MCU: Detecting Small Objects in Real-Time on Microcontroller Units
Liam Boyle, Julian Moosmann, Nicolas Baumann +2
Advances in lightweight neural networks have revolutionized computer vision in a broad range of IoT applications, encompassing remote monitoring and process automation. However, th…
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…