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Real-time unmanned aerial vehicle (UAV) acoustic detection at the edge demands low-latency inference under strict power and hardware limits. This paper presents SHIELD8-UAV, a sequential 8-bit hardware implementation of a precision-aware 1D…
Advances in lightweight neural networks have revolutionized computer vision in a broad range of IoT applications, encompassing remote monitoring and process automation. However, the detection of small objects, which is crucial for many of…
We present the commissioning of the Fast Annihilation Cryogenic Tracker detector (FACT), installed around the antihydrogen production trap inside the 1 T superconducting magnet of the AE\=gIS experiment. FACT is designed to detect pions…
Achieving faster execution with shorter compilation time can foster further diversity and innovation in neural networks. However, the current paradigm of executing neural networks either relies on hand-optimized libraries, traditional…
Running deep learning models on resource-constrained edge devices has drawn significant attention due to its fast response, privacy preservation, and robust operation regardless of Internet connectivity. While these devices already cope…
We describe the design concept and estimated performance of an iron-scintillator sampling calorimeter for the future Electron Ion Collider. The novel aspect of this detector is a multi-dimensional readout coupled with foreseen excellent…
Intelligent edge vision tasks encounter the critical challenge of ensuring power and latency efficiency due to the typically heavy computational load they impose on edge platforms.This work leverages one of the first "AI in sensor" vision…
The BULLKID-DM experiment aims to detect WIMP-like potential Dark Matter particles with masses below 1 GeV/c^2. Sensing these particles is challenging, as it requires nuclear recoil detectors characterized by high exposure and an energy…
Surface defects on Printed Circuit Boards (PCBs) directly compromise product reliability and safety. However, achieving high-precision detection is challenging because PCB defects are typically characterized by tiny sizes, high texture…
The next wave of on-device AI will likely require energy-efficient deep neural networks. Brain-inspired spiking neural networks (SNN) has been identified to be a promising candidate. Doing away with the need for multipliers significantly…
This paper introduces an effective solution for retrofitting construction power tools with low-power IoT to enable accurate activity classification. We address the challenge of distinguishing between when a power tool is being moved and…
The MicroBooNE continuous readout stream is a parallel readout of the MicroBooNE liquid argon time projection chamber (LArTPC) which enables detection of non-beam events such as those from a supernova neutrino burst. The low energies of the…
Cluster counting dN/dx is a promising method to enhance particle identification for gaseous detectors, especially in next-generation collider experiments like the FCC-ee, where good pion-kaon separation over a broad momentum range is…
This study introduces a new Scintillator Simulation Library called SSLG4 for the Geant4 Monte Carlo simulation package. With SSLG4, we aim to enhance efficiency and accelerate progress in optical simulations within the Geant4 framework by…
The CONCERTO millimeter-wave spectral-imaging instrument was deployed on the Atacama Pathfinder EXperiment (APEX), where it acquired science data between April 2021 and May 2023. The instrument features two focal-plane arrays, each composed…
The Omicron software is a tool developed to perform a multi-resolution time-frequency analysis of data from gravitational-wave detectors: the LIGO, Virgo, and KAGRA detectors. Omicron generates spectrograms from whitened data streams,…
Demand for efficient onboard object detection is increasing due to its key role in autonomous navigation. However, deploying object detection models such as YOLO on resource constrained edge devices is challenging due to the high…
Current, state-of-the-art CCDs are close to being able to deliver all key performance figures for future strategic X-ray missions except for the required frame rates. Our Stanford group is seeking to close this technology gap through a…
In this paper, we present development of a portable cosmic muon tracker tailored for both on-site measurements of cosmic muon flux as well as for outreach activities. The tracker comprises of two 70 mm x 70 mm plastic scintillators,…
The SoLid collaboration have developed an intelligent readout system to reduce their 3200 silicon photomultiplier detector's data rate by a factor of 10000 whilst maintaining high efficiency for storing data from anti-neutrino interactions.…