39 citations · 90 across the 12 of their papers we have counts for
13 papers
An Energy-Proportional Multimodal and Context-Aware Vision IoT Node
Julian Moosmann, Philipp Mayer, Luca Benini +1
While recent advancements in TinyML have significantly reduced the computational complexity of on-device vision pipelines, image acquisition remains a dominant contributor to syste…
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…
A Miniaturized In-Mouth pH Sensing System for Real-Time Intraoral Telemetry
Lukas Schulthess, Philipp Schilk, Julian Moosmann +4
Dental caries is one of the most common chronic diseases worldwide, caused by acid production from bacterial metabolism of fermentable carbohydrates and affecting people of all age…
Bridging Generalization and Personalization in Human Activity Recognition via On-Device Few-Shot Learning
Pixi Kang, Julian Moosmann, Mengxi Liu +4
Human Activity Recognition (HAR) with different sensing modalities requires both strong generalization across diverse users and efficient personalization for individuals. However,…
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…
On-device Learning of EEGNet-based Network For Wearable Motor Imagery Brain-Computer Interface
Sizhen Bian, Pixi Kang, Julian Moosmann +4
Electroencephalogram (EEG)-based Brain-Computer Interfaces (BCIs) have garnered significant interest across various domains, including rehabilitation and robotics. Despite advancem…
On-Device Training Empowered Transfer Learning For Human Activity Recognition
Pixi Kang, Julian Moosmann, Sizhen Bian +1
Human Activity Recognition (HAR) is an attractive topic to perceive human behavior and supplying assistive services. Besides the classical inertial unit and vision-based HAR method…
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…