Related papers: Deep learning solutions to telescope pointing and …
Object re-identification (ReID) from images plays a critical role in application domains of image retrieval (surveillance, retail analytics, etc.) and multi-object tracking (autonomous driving, robotics, etc.). However, systems that…
Optical alignment and testing of the Integrated Science Instrument Module of the James Webb Space Telescope is underway. We describe the Optical Telescope Element Simulator used to feed the science instruments with point images of precisely…
Developing lightweight Deep Convolutional Neural Networks (DCNNs) and Vision Transformers (ViTs) has become one of the focuses in vision research since the low computational cost is essential for deploying vision models on edge devices.…
We present DeepStreaks, a convolutional-neural-network, deep-learning system designed to efficiently identify streaking fast-moving near-Earth objects that are detected in the data of the Zwicky Transient Facility (ZTF), a wide-field,…
Over the past ten years, several breakthroughs have been made in multi-messenger astronomy. Thanks to the IceCube Neutrino Observatory, the detection of astrophysical neutrinos was proved to be practical. However, due to the limited…
Determining accurate bird's eye view (BEV) positions of objects and tracks in a scene is vital for various perception tasks including object interactions mapping, scenario extraction etc., however, the level of supervision required to…
High-resolution beam telescopes for charged particle tracking are one of the most important and equally demanding infrastructure items at test beam facilities. The main purpose of beam telescopes is to provide precise reference track…
The installation of the muon telescope detector opened new possibilities for studying dimuon production at STAR. However, backgrounds from hadron punch-through and weak decays of pions and kaons make the identification of primary muons…
Calibrating the optical properties within the detection medium of a neutrino telescope is crucial for determining its angular resolution and energy scale. For the next generation of neutrino telescopes planned to be constructed in deep…
Training high-accuracy 3D detectors necessitates massive labeled 3D annotations with 7 degree-of-freedom, which is laborious and time-consuming. Therefore, the form of point annotations is proposed to offer significant prospects for…
(Abridged) Context: In the previous paper in this series, we identified that a pentagonal arrangement of five telescopes, using a kernel-nulling beam combiner, shows notable advantages for some important performance metrics for a…
Deep Neural Networks (DNNs) are a promising tool for Global Navigation Satellite System (GNSS) positioning in the presence of multipath and non-line-of-sight errors, owing to their ability to model complex errors using data. However,…
Doing astronomy with photons of energies in excess of a GeV has turned out to be extremely challenging. Efforts are underway to develop instruments that may push astronomy to wavelengths smaller than $10^{-14}$~cm by mapping the sky in high…
Precise physical properties of the known transiting exoplanets are essential for their precise atmospheric characterization using modern and upcoming instruments. Leveraging the large volume of high SNR photometric follow-up data from TESS,…
Accurate reconstruction of magnetic fields in inaccessible regions is vital for many high-precision experiments in physics. Traditional methods, such as spherical harmonic expansion, often suffer from truncation errors that limit their…
In the last decade, over a million stars were monitored to detect transiting planets. Manual interpretation of potential exoplanet candidates is labor intensive and subject to human error, the results of which are difficult to quantify.…
The use of Adaptive Optics in Extremely Large Telescopes brings new challenges, one of which is the treatment of Shack-Hartmann Wavefront sensors images. When using this type of sensors in conjunction with laser guide stars for sampling the…
Light-field microscopes are able to capture spatial and angular information of incident light rays. This allows reconstructing 3D locations of neurons from a single snap-shot.In this work, we propose a model-inspired deep learning approach…
Construction of EUDET pixel telescope will significantly improve the test beam infrastructure for the ILC vertex detector studies. The telescope, based on the Monolithic Active Pixel Sensors (MAPS), will consist of up to six readout planes…
Recent methods for 3D reconstruction and rendering increasingly benefit from end-to-end optimization of the entire image formation process. However, this approach is currently limited: effects of the optical hardware stack and in particular…