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We propose a neural inverse rendering approach that jointly reconstructs geometry, spatially varying reflectance, and lighting conditions from multi-view images captured under varying directional lighting. Unlike prior multi-view…
A method is presented for estimating the background at a given location on a sky map by interpolating the estimated background from a set of concentric annuli which surround this location. If the background is nonuniform but smoothly…
Neutron spectroscopy is an invaluable tool for many scientific and industrial applications, including underground Dark Matter searches. Neutron-induced backgrounds produced by cosmic ray muons and the cavern radioactivity can mimic the…
We focus on an alignment-free method to estimate the underlying signal from a large number of noisy randomly shifted observations. Specifically, we estimate the mean, power spectrum, and bispectrum of the signal from the observations. Since…
This paper addresses the problem of unsupervised soft bit error rate (BER) estimation for any communications system, where no prior knowledge either about transmitted information bits, or the transceiver scheme is available. We show that…
We discuss a new method to extract neutrino signals in low energy experiments. In this scheme the symmetric nature of most backgrounds allows for direct cancellation from data. The application of this technique to the Palo Verde reactor…
A hybrid estimator of the log-spectral density of a stationary time series is proposed. First, a multiple taper estimate is performed, followed by kernel smoothing the log-multitaper estimate. This procedure reduces the expected mean square…
The CLEAN algorithm, widely used in radio interferometry for the deconvolution of radio images, performs well only if the raw radio image (dirty image) is, to good approximation, a simple convolution between the instrumental point-spread…
This paper investigates the performance of the adaptive matched filtering (AMF) in cluttered environments, particularly when operating with superimposed signals. Since the instantaneous signal-to-clutter-plus-noise ratio (SCNR) is a random…
Intelligent reflecting surface (IRS) has become a promising technology to aid next generation wireless communication systems. In this paper, we develop an alternating beamforming technique with a novel concept of IRS element allocation for…
Neutron spectrum and scattered neutrons caused distortions are major problems in fast neutron radiography and should be considered for improving the image quality. This paper puts emphasis on the removal of these image distortions and…
Automatic Modulation Recognition (AMR) detects modulation schemes of received signals for further processing of signals without any priori information, which is critically important for civil spectrum regulation, information countermea…
In an attempt to address the need for skilled clinicians in heart sound interpretation, recent research efforts on automating cardiac auscultation have explored deep learning approaches. The majority of these approaches have been based on…
Aberration-corrected Scanning Transmission Electron Microscopy (STEM) has become an essential tool in understanding materials at the atomic scale. However, tuning the aberration corrector to produce a sub-{\AA}ngstr\"om probe is a complex…
Background modeling is widely used for intelligent surveillance systems to detect moving targets by subtracting the static background components. Most roadside LiDAR object detection methods filter out foreground points by comparing new…
Automatic Modulation Recognition (AMR) is critical in identifying various modulation types in wireless communication systems. Recent advancements in deep learning have facilitated the integration of algorithms into AMR techniques. However,…
In a recent work [Phys. Rev. Lett. 116, 240401 (2016)], a framework known by the name of "assemblage moment matrices" (AMMs) has been introduced for the device-independent quantification of quantum steerability and measurement…
Spectral algorithms leverage spectral regularization techniques to analyze and process data, providing a flexible framework for addressing supervised learning problems. To deepen our understanding of their performance in real-world…
In this short communication, we revise and refine our previous articles on this topic to simplify the modifications to the angle-resolved photoemission spectroscopy (ARPES) spectrometers required to finally implement our idea, with minimal…
Some high-energy experiments have suffered from synchrotron-radiation background. As a measure, we have developed a new calculation method of synchrotron radiation based on a real beam orbit, aiming at quantitative estimations and the…