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Machine learning (ML) and tensor-based methods have been of significant interest for the scientific community for the last few decades. In a previous work we presented a novel tensor-based system identification framework to ease the…

Machine Learning · Computer Science 2023-06-30 Oliver Ploder , Christina Auer , Oliver Lang , Thomas Paireder , Mario Huemer

Tomographic imaging is useful for revealing the internal structure of a 3D sample. Classical reconstruction methods treat the object of interest as a vector to estimate its value. Such an approach, however, can be inefficient in analyzing…

Applications · Statistics 2022-04-06 Sanket R. Jantre , Zichao Wendy Di

We have developed an improved method of time-resolved x-ray reflectivity (XRR) using monochromatic synchrotron radiation. Our method utilizes a polycapillary x-ray optic to create a range of incident angles and an area detector to collect…

Materials Science · Physics 2019-03-27 Howie Joress , Shane Quinlan Arlington , Timothy P. Weihs , Joel D. Brock , Arthur Woll

X-ray interaction with matter is an energy-dependent process that is contingent on the atomic structure of the constituent material elements. The most advanced models to capture this relationship currently rely on Monte Carlo (MC)…

Machine Learning · Computer Science 2023-07-11 Raziye Kubra Kumrular , Thomas Blumensath

We develop a method based on the cross-spectrum of an intensity-modulated CW laser, which can extract a signal from an extremely noisy environment and image objects hidden in turbid media. We theoretically analyzed our scheme and performed…

Scanning near-field optical microscopy is one of the most effective techniques for spectroscopy of nanoscale systems. However, inferring optical constants from the measured near-field signal can be challenging because of a complicated and…

Optics · Physics 2023-04-19 Yueqi Zhao , Xinzhong Chen , Ziheng Yao , Mengkun Liu , Michael M. Fogler

We present the first deterministic, finite-step algorithm for exact tensor ring (TR) decomposition, addressing an open question about the existence of such procedures. Our method leverages blockwise simultaneous diagonalization to recover…

Numerical Analysis · Mathematics 2025-12-02 Han Chen , Sitan Chen , Anru R. Zhang

Contour tracking in adverse environments is a challenging problem due to cluttered background, illumination variation, occlusion, and noise, among others. This paper presents a robust contour tracking method by contributing to some of the…

Computer Vision and Pattern Recognition · Computer Science 2015-03-17 Peihua Li

Gabor wavelet is an essential tool for image analysis and computer vision tasks. Local structure tensors with multiple scales are widely used in local feature extraction. Our research indicates that the current corner detection method based…

Computer Vision and Pattern Recognition · Computer Science 2023-03-09 Huaqing Wang , Junfeng Jing , Ning Li , Weichuan Zhang , Chao Liu

The propagation of coherent light in multimode optical fibers results in a speckled output that is both complex and sensitive to environmental effects. These properties can be a powerful tool for sensing, as small perturbations lead to…

Inspired by the extensive application of terahertz imaging technologies in the field of aerospace, we exploit a terahertz frequency modulated continuous wave imaging method with continuous wavelet transform algorithm to detect a multilayer…

Signal Processing · Electrical Eng. & Systems 2019-05-30 Yu Zhou

We describe a full-field coherent imaging approach suitable for hard X-rays based on a classical (i.e. Galilean) X-ray microscope. The method combines a series of low-resolution images acquired at different transverse lens positions into a…

Optics · Physics 2019-05-07 Carsten Detlefs , Mario A. Beltran , Jean-Pierre Guigay , Hugh Simons

Radio-frequency (RF) tomographic imaging is a promising technique for inferring multi-dimensional physical space by processing RF signals traversed across a region of interest. However, conventional RF tomography schemes are generally based…

Information Theory · Computer Science 2017-12-19 Tao Deng , Xiao-Yang Liu , Feng Qian , Anwar Walid

We propose a method for remotely detecting backward reflection via induced decay of cold dark matter such as axion in the background of a propagating coherent photon field. This method can be particularly useful for probing concentrated…

High Energy Physics - Phenomenology · Physics 2024-08-21 Kensuke Homma

In cognitive radio systems, the ability to accurately detect primary user's signal is essential to secondary user in order to utilize idle licensed spectrum. Conventional energy detector is a good choice for blind signal detection, while it…

Information Theory · Computer Science 2019-09-09 Jiabao Gao , Xuemei Yi , Caijun Zhong , Xiaoming Chen , Zhaoyang Zhang

The fields of view of Extremely Large Telescopes will contain vast numbers of spatial sampling elements (spaxels) as their Adaptive Optics systems approach the diffraction limit over wide fields. Since this will exceed the detection…

Instrumentation and Methods for Astrophysics · Physics 2015-05-13 G. J. Murray , J. R. Allington-Smith

Methods for reconstructing the spectral density of a vibrational environment from experimental data can yield key insights into the impact of the environment on molecular function. Although such experimental methods exist, they generally…

Chemical Physics · Physics 2025-09-11 Roosmarijn de Wit , Jonathan Keeling , Brendon W. Lovett , Alex W. Chin

Although speckle is a powerful tool for high-precision metrology, large datasets and cumbersome training are always required to learn from the encoded speckle patterns, which is unfavorable for rapid deployment and multi-dimensional…

When a macroscopic-sized non-crystalline sample is illuminated using coherent x-ray radiation, a bifurcation of photon energy flow may occur. The coarse-grained complex refractive index of the sample may be considered to attenuate and…

SAR image classification naturally has to deal with huge noise and a high dynamic range particularly requiring robust classification models. Additionally, the deployment of these models on edge devices, such as drones and military aircraft,…

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