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The price of instruments and observing time on modern telescopes is quickly increasing with the size of the primary mirror. Therefore, it is worth revisiting the data reduction algorithms to extract every bit of scientific information from…
Implicit Neural Representations (INRs) have revolutionized signal processing and computer vision by modeling signals as continuous, differentiable functions parameterized by neural networks. However, INRs are prone to the spectral bias…
Recently, a novel structures of reconfigurable intelligent surface (RIS) integrating both passive and active elements, termed reconfigurable intelligent sensing surface (RISS), efficiently addresses challenges in RIS channel estimation and…
The Interstellar Boundary Explorer (IBEX) satellite has been in orbit since 2008 and detects energy-resolved energetic neutral atoms (ENAs) originating from the heliosphere. Different regions of the heliosphere generate ENAs at different…
The EUV Imaging Spectrometer (EIS) instrument on board the Hinode satellite has access to some of the best coronal density diagnostics and the high sensitivity of the instrument now allows electron number density, N_e, measurements to an…
Context: New spectroscopic surveys will increase the number of astronomical objects requiring characterization by over tenfold.. Machine learning tools are required to address this data deluge in a fast and accurate fashion. Most machine…
Intelligent reflecting surface (IRS) is a promising technology for enhancing wireless communication systems. It adaptively configures massive passive reflecting elements to control wireless channel in a desirable way. Due to hardware…
Inferior soft-tissue contrast resolution is a major limitation of current CT scanners. The aim of the study is to improve the contrast resolution of CT scanners using dual-energy acquisition. Based on dual-energy material decomposition, the…
Intelligent Reflecting Surface (IRS) has been recently proposed as a promising solution to enhance the spectral and energy efficiency of future wireless networks by tuning a massive number of low-cost passive reflecting elements and thereby…
Spectrum sensing enables cognitive radio systems to detect unused portions of the radio spectrum and then use them while avoiding interferences to the primary users. Energy detection is one of the most used techniques for spectrum sensing…
Learning with noisy labels aims to ensure model generalization given a label-corrupted training set. The sample selection strategy achieves promising performance by selecting a label-reliable subset for model training. In this paper, we…
A scheme for a surface plasmon resonance system under conditions of electromagnetically induced transparency (EIT) is proposed. The system is composed of three layers: a prism, a thin metal film, and a hybrid dielectric consisting of EIT…
Implicit Neural Representations (INRs) model continuous signals using multilayer perceptrons (MLPs), enabling compact, differentiable, and high-fidelity representations of data across diverse domains. However, due to the low-frequency bias…
In the past as well as present wireless communication systems, the wireless propagation environment is regarded as an uncontrollable black box that impairs the received signal quality, and its negative impacts are compensated for by relying…
Precision in identifying and differentiating micro and macro blood vessels in the retina is crucial for the diagnosis of retinal diseases, although it poses a significant challenge. Current autoencoding-based segmentation approaches…
The NIO1 experiment hosts a flexible RF H- ion source, developed by INFN-LNL and Consorzio RFX to improve the present concepts for the production and acceleration of negative ions. The source is also used to benchmark the instrumentation…
We introduce a new pipeline for analyzing and mitigating radio frequency interference (RFI), which we call Sky-Subtracted Incoherent Noise Spectra (SSINS). SSINS is designed to identify and remove faint RFI below the single baseline thermal…
The Infrared Spectrograph (IRS) is one of three science instruments on the Spitzer Space Telescope. The IRS comprises four separate spectrograph modules covering the wavelength range from 5.3 to 38micron with spectral resolutions, R \~90…
High-quality saliency maps are essential in several machine learning application areas including explainable AI and weakly supervised object detection and segmentation. Many techniques have been developed to generate better saliency using…
Electrochemical Impedance Spectroscopy (EIS) is a crucial technique for assessing corrosion of a metallic materials. The analysis of EIS hinges on the selection of an appropriate equivalent circuit model (ECM) that accurately characterizes…