Related papers: Demonstration of Sub-micron UCN Position Resolutio…
Accurately tracking particles and determining their coordinate along the optical axis is a major challenge in optical microscopy, especially when extremely high precision is needed. In this study, we introduce a deep learning approach using…
In this work, we have developed and characterized a position-sensitive CLYC detector that acts as the neutron imaging layer and $\gamma$-ray Compton scatterer of the novel dual \g-ray and neutron imaging system GN-Vision, which aims at…
We have been developing a neutron detector with spatial resolution of submicron by loading 6Li into fine-grained nuclear emulsion. By exposure to thermal neutrons, tracks from neutron capture events were observed. From their grain density,…
Matching sonar images with high accuracy has been a problem for a long time, as sonar images are inherently hard to model due to reflections, noise and viewpoint dependence. Autonomous Underwater Vehicles require good sonar image matching…
Oscillations of the neutron into a hidden sector particle are processes predicted in various Standard Model extensions. This extra channel for neutron disappearance has not been tested experimentally in large portions of the oscillation…
This article presents an innovative study in exploring, evaluating, and implementing deep learning architectures for the calibration of multi-modal sensor systems. The focus behind this is to leverage the use of sensor fusion to achieve…
We have developed a prototype time-resolved neutron imaging detector employing the micro-pixel chamber (muPIC), a micro-pattern gaseous detector, coupled with a field programmable gate array-based data acquisition system for applications in…
Identifying the positions of granular particles from experimental images is often complicated by their partial overlap in two dimensional projections. Uneven backgrounds and inhomogeneous illuminations can add to the challenge. Conventional…
Under-display cameras (UDCs) allow for full-screen designs by positioning the imaging sensor underneath the display. Nonetheless, light diffraction and scattering through the various display layers result in spatially varying and complex…
Convolutional Neural Networks (CNNs) have become the state-of-the-art in various computer vision tasks, but they are still premature for most sensor data, especially in pervasive and wearable computing. A major reason for this is the…
Progress has been achieved recently in object detection given advancements in deep learning. Nevertheless, such tools typically require a large amount of training data and significant manual effort to label objects. This limits their…
Ultracold neutrons (UCNs) are a useful tool for fundamental physics experiments. They can be used to probe the lifetime of free neutrons, search for new CP violating processes and exotic interactions beyond the Standard Model, perform…
We have developed an image-based convolutional neural network (CNN) that is applicable for quantitative time-resolved measurements of the fragmentation behavior of opaque brittle materials using ultra-high speed optical imaging. This model…
Pervasive localization is essential for continuous tracking applications, yet existing solutions face challenges in balancing power consumption and accuracy. GPS, while precise, is impractical for continuous tracking of micro-assets due to…
We present the first measurements of the survival time of ultracold neutrons (UCNs) in solid deuterium SD2. This critical parameter provides a fundamental limitation to the effectiveness of superthermal UCN sources that utilize solid…
Unmanned Surface Vehicles (USVs) are pivotal in marine exploration, but their sensors' accuracy is compromised by the dynamic marine environment. Traditional calibration methods fall short in these conditions. This paper introduces a deep…
Image decomposition plays a crucial role in various computer vision tasks, enabling the analysis and manipulation of visual content at a fundamental level. Overlapping images, which occur when multiple objects or scenes partially occlude…
Recent interest in on-orbit servicing and Active Debris Removal (ADR) missions have driven the need for technologies to enable non-cooperative rendezvous manoeuvres. Such manoeuvres put heavy burden on the perception capabilities of a…
In the UCN{\tau} experiment, ultracold neutrons (UCN) are confined by magnetic fields and the Earth's gravitational field. Field-trapping mitigates the problem of UCN loss on material surfaces, which caused the largest correction in prior…
In the present paper, we propose a source camera identification method for mobile devices based on deep learning. Recently, convolutional neural networks (CNNs) have shown a remarkable performance on several tasks such as image recognition,…