Related papers: Enhancing Ly{\alpha} Emitter Identification in HET…
Background and Aim: Over-fitting issue has been the reason behind deep learning technology not being successfully implemented in oral cancer images classification. The aims of this research were reducing overfitting for accurately producing…
We present a spectroscopic survey of Ly$\alpha$ emitters in the Extended Groth Strip (EGS) field, targeting the regime near the Epoch of Reionization. Using Keck/DEIMOS, we observed 947 high-$z$ candidates with photometric redshifts from 3…
High-resolution transmission electron microscopy (HRTEM) is crucial for observing material's structural and morphological evolution at Angstrom scales, but the electron beam can alter these processes. Devices such as CMOS-based…
Epilepsy is one of the most common neurological disorders. This disease requires reliable and efficient seizure detection methods. Electroencephalography (EEG) is the gold standard for seizure monitoring, but its manual analysis is a…
Deep Learning (DL) is a machine learning procedure for artificial intelligence that analyzes the input data in detail by increasing neuron sizes and number of the hidden layers. DL has a popularity with the common improvements on the…
We present rest-frame Ly$\alpha$ equivalent widths (EW) of 417 Ly$\alpha$ emitters (LAEs) detected with Multi Unit Spectroscopic Explorer (MUSE) on the Very Large Telescope (VLT) at $2.9 < z < 6.6$ in the Hubble Ultra Deep Field. Based on…
Lyman Alpha Emitters (LAEs) are star-forming galaxies that efficiently probe the spatial distribution of galaxies in the high redshift universe. The spatial clustering of LAEs reflects the properties of their individual host dark matter…
This paper proposes a learnable nonlinear activation mechanism specifically for convolutional neural network (CNN) termed as LENI, which learns to enhance the negative information in CNNs. In sharp contrast to ReLU which cuts off the…
Image deblurring aims to recover the latent sharp image from its blurry counterpart and has a wide range of applications in computer vision. The Convolution Neural Networks (CNNs) have performed well in this domain for many years, and until…
Hardware imperfections in RF transmitters introduce features that can be used to identify a specific transmitter amongst others. Supervised deep learning has shown good performance in this task but using datasets not applicable to real…
In this work, I framed the Renyi and Tsallis Holographic Dark Energy (HDE) models within the presence of a spatially flat and isotropic FRW model filled with matter and dark energy in teleparallel gravity. The energy densities of Renyi HDE…
We present a narrowband survey with three adjacent filters for z=2.8--2.9 Lyman Alpha Emitter (LAE) galaxies in the Extended Chandra Deep Field South (ECDFS), along with spectroscopic followup. With a complete sample of 96 LAEs in the…
We present the $ugriz$-band Dark Energy Camera (DECam) plus 3.6 and 4.5 $\mu$m IRAC catalogs for the Spitzer/HETDEX Exploratory Large-Area (SHELA) survey. SHELA covers $\sim24$ deg$^{2}$ of the Sloan Digital Sky Survey (SDSS) Stripe 82…
The low-frequency component of the upcoming Square Kilometre Array Observatory (SKA-Low) will be sensitive enough to construct 3D tomographic images of the 21-cm signal distribution during reionisation. However, foreground contamination…
This work proposes a spectral convolutional neural network (CNN) operating on laser induced breakdown spectroscopy (LIBS) signals to learn to (1) disentangle spectral signals from the sources of sensor uncertainty (i.e., pre-process) and…
We present the largest area survey to date (1.4 deg2) for Lyman-alpha emitters (LAEs) at z~9, as part of the Hi-z Emission Line Survey (HiZELS). The survey, which primarily targets H-alpha emitters at z < 3, uses the Wide Field CAMera on…
In routine colorectal cancer management, histologic samples stained with hematoxylin and eosin are commonly used. Nonetheless, their potential for defining objective biomarkers for patient stratification and treatment selection is still…
Extremely Large-scale Array (ELAA) is considered a frontier technology for future communication systems, pivotal in improving wireless systems' rate and spectral efficiency. As ELAA employs a multitude of antennas operating at higher…
Recent interest in New Early Dark Energy (NEDE), a cosmological model with a vacuum energy component decaying in a triggered phase transition around recombination, has been sparked by its impact on the Hubble tension. Previous constraints…
In H-mode tokamak plasmas, the plasma is sometimes ejected beyond the edge transport barrier. These events are known as edge localized modes (ELMs). ELMs cause a loss of energy and damage the vessel walls. Understanding the physics of ELMs…