Related papers: Binary Classification of Light and Dark Time Trace…

The CYGNO experiment employs an optical-readout Time Projection Chamber (TPC) to search for rare low-energy interactions using finely resolved scintillation images. While the optical readout provides rich topological information, it…

In the search for neutrinoless double-beta decay, the high-pressure gaseous Time Projection Chamber has a distinct advantage, because the ionization charge tracks produced by particle interactions are extended and the detector captures the…

The XENON1T experiment uses a time projection chamber (TPC) with liquid Xenon to search for Weakly Interacting Massive Particles (WIMPs), a proposed Dark Matter particle, via direct detection. As this experiment relies on capturing rare…

The wealth of smartphone data collected by the Cosmic Ray Extremely Distributed Observatory(CREDO) greatly surpasses the capabilities of manual analysis. So, efficient means of rejectingthe non-cosmic-ray noise and identification of signals…

Several ongoing and upcoming radio telescopes aim to detect either the global 21 cm signal or the 21 cm power spectrum. The extragalactic radio background, as detected by ARCADE-2 and LWA-1, suggests a strong radio background from cosmic…

This work presents and analyzes three convolutional neural network (CNN) models for efficient pixelwise classification of images. When using convolutional neural networks to classify single pixels in patches of a whole image, a lot of…

We present a study of the potential for Convolutional Neural Networks (CNNs) to enable separation of astrophysical transients from image artifacts, a task known as "real-bogus" classification without requiring a template subtracted (or…

A white noise analysis of modern deep neural networks is presented to unveil their biases at the whole network level or the single neuron level. Our analysis is based on two popular and related methods in psychophysics and neurophysiology…

In light-shining-through-walls experiments, axions and axion-like particles (ALPs) are searched for by exposing an optically thick barrier to a laser beam. In a magnetic field, photons could convert into ALPs in front of the barrier and…

Next-generation neutrinoless double beta decay experiments aim for half-life sensitivities of ~$10^{27}$ yr, requiring suppressing backgrounds to <1 count/tonne/yr. For this, any extra background rejection handle, beyond excellent energy…

The Transiting Exoplanet Survey Satellite (TESS) mission measured light from stars in ~75% of the sky throughout its two year primary mission, resulting in millions of TESS 30-minute cadence light curves to analyze in the search for…

A neural network method is developed to discriminate direct photons from the neutral pion background in the PHOS spectrometer of the ALICE experiment at the LHC collider. The neural net has been trained to distinguish different classes of…

Convolutional Neural Networks (CNNs) provide excellent performance when used for image classification. The classical method of training CNNs is by labeling images in a supervised manner as in "input image belongs to this label" (Positive…

This paper presents the effectiveness of convolutional neural network (CNN) to classify power quality problems. These problems arise mainly due to increase in use of non-linear loads, operation of devices like adjustable speed drives and…

Navigation and mobility are some of the major problems faced by visually impaired people in their daily lives. Advances in computer vision led to the proposal of some navigation systems. However, most of them require expensive and/or heavy…

Deep learning using convolutional neural networks (CNNs) is quickly becoming the state-of-the-art for challenging computer vision applications. However, deep learning's power consumption and bandwidth requirements currently limit its…

CNNs have become one of the most commonly used computational tool in the past two decades. One of the primary downsides of CNNs is that they work as a ``black box", where the user cannot necessarily know how the image data are analyzed, and…

We propose the use of transition-edge sensor (TES) single-photon detectors as a simultaneous target and sensor for direct dark matter searches, and report results from the first search of this kind. We perform a 489 h science run with a TES…

We present an application of computer vision methods to classify the light curves of eclipsing binaries (EB). We have used pre-trained models based on convolutional neural networks ($\textit{ResNet50}$) and vision transformers…

In modern artificial intelligence, convolutional neural networks (CNNs) have become a cornerstone for visual and perceptual tasks. However, their implementation on conventional electronic hardware faces fundamental bottlenecks in speed and…