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The modeling of realistic magnetic materials requires the inclusion of defects. Based on the pseudospectral Landau-Lifshitz description of magnetisation dynamics, we propose a statistical model that takes into account defects, specifically…

Mesoscale and Nanoscale Physics · Physics 2026-03-12 C. Eagan , M. Copus , E. Iacocca

Full-waveform inversion (FWI) is an advanced technique for reconstructing high-resolution subsurface physical parameters by progressively minimizing the discrepancy between observed and predicted seismic data. However, conventional FWI…

Geophysics · Physics 2025-03-04 Chao Song , Tariq Alkhalifah , Umair Bin Waheed , Silin Wang , Cai Liu

Accurate three-dimensional perception is essential for modern industrial robotic systems that perform manipulation, inspection, and navigation tasks. RGB-D and stereo vision sensors are widely used for this purpose, but the depth maps they…

Computer Vision and Pattern Recognition · Computer Science 2025-12-10 Tony Salloom , Dandi Zhou , Xinhai Sun

Radar sounders are electromagnetic instruments that can probe deep into the subsurface of Earth and other planetary bodies by processing the echo of transmitted radar waves. Conventional approaches for analyzing such data rely on…

Signal Processing · Electrical Eng. & Systems 2026-05-12 Jordy Dal Corso , Annalena Kofler , Marco Cortellazzi , Lorenzo Bruzzone , Bernhard Schölkopf

The determination of accurate bathymetric information is a key element for near offshore activities, hydrological studies such as coastal engineering applications, sedimentary processes, hydrographic surveying as well as archaeological…

Computer Vision and Pattern Recognition · Computer Science 2020-02-19 Panagiotis Agrafiotis , Dimitrios Skarlatos , Andreas Georgopoulos , Konstantinos Karantzalos

A derivation of the properties of pulsed radiative imaging systems is presented with examples drawn from conventional, synthetic aperture, and interferometric radar. A geometric construction of the space and time components of a radar…

Optics · Physics 2009-11-07 Andrew K. Gabriel

In this paper, a sparsity-aware adaptive algorithm for distributed learning in diffusion networks is developed. The algorithm follows the set-theoretic estimation rationale. At each time instance and at each node of the network, a closed…

Information Theory · Computer Science 2015-06-03 Symeon Chouvardas , Konstantinos Slavakis , Yannis Kopsinis , Sergios Theodoridis

This paper presents a new approach to detecting road boundaries based on sparse radar signals. We model the roadway using a homogeneous model and derive its conditional predictive model under known radar motion. Using the conditional…

Robotics · Computer Science 2023-09-18 Aaron Kingery , Dezhen Song

Single image super-resolution traditionally assumes spatially-invariant degradation models, yet real-world imaging systems exhibit complex distance-dependent effects including atmospheric scattering, depth-of-field variations, and…

Computer Vision and Pattern Recognition · Computer Science 2025-10-30 Tianhao Guo , Bingjie Lu , Feng Wang , Zhengyang Lu

Multi-channel Analysis of Surface Waves (MASW) is a seismic method employed to obtain useful information about shear-wave velocities in the near surface. A fundamental step in this methodology is the extraction of dispersion curves from…

We propose and test the Direct Waveform Inversion (DWI) scheme to simultaneously invert for layered velocity and density profiles, using reflection seismic waveforms recorded on the surface. The recorded data include primary reflections and…

Geophysics · Physics 2021-08-10 Zhonghan Liu , Yingcai Zheng , Hua-Wei Zhou

This paper proposes a depth estimation method using radar-image fusion by addressing the uncertain vertical directions of sparse radar measurements. In prior radar-image fusion work, image features are merged with the uncertain sparse…

Computer Vision and Pattern Recognition · Computer Science 2024-03-26 Masaya Kotani , Takeru Oba , Norimichi Ukita

The design and implementation of low-profile antennas has been analyzed in past decades from different perspectives while the purpose is to have a small size in the device, and an adequate electromagnetic behavior. This work pursues a…

Signal Processing · Electrical Eng. & Systems 2020-11-25 Enrique Lizarraga , Walter Herrera

Neural implicit representations have emerged as a powerful paradigm for 3D reconstruction. However, despite their success, existing methods fail to capture fine geometric details and thin structures, especially in scenarios where only…

Computer Vision and Pattern Recognition · Computer Science 2025-04-23 Aarya Patel , Hamid Laga , Ojaswa Sharma

We present the Seismic Laboratory for Imaging and Modeling/Monitoring (SLIM) open-source software framework for computational geophysics and, more generally, inverse problems involving the wave-equation (e.g., seismic and medical…

The identification of material parameters occurring in constitutive models has a wide range of applications in practice. One of these applications is the monitoring and assessment of the actual condition of infrastructure buildings, as the…

Machine Learning · Computer Science 2023-06-14 David Anton , Henning Wessels

Full-waveform inversion (FWI) is a widely used technique in seismic processing to produce high resolution Earth models that fully explain the recorded seismic data. FWI is a local optimisation problem which aims to minimise in a…

Geophysics · Physics 2019-11-22 Christopher Zerafa , Pauline Galea , Cristiana Sebu

Surface wave tomography uses measured dispersion properties of surface waves to infer the spatial distribution of subsurface properties such as shear-wave velocities. These properties can be estimated vertically below any geographical…

Geophysics · Physics 2020-08-26 Stephanie Earp , Andrew Curtis , Xin Zhang , Fredrik Hansteen

Recent advances in meta-optics have enabled diverse functionalities in compact optical devices; however, conventional forward design approaches become inadequate as device complexity and scale grow. Inverse design offers a powerful…

We present a new seismic inversion method that uses deep learning (DL) features for the subsurface velocity model estimation. The DL feature is a low-dimensional representation of the high-dimensional seismic data, which is automatically…

Geophysics · Physics 2021-10-04 Yuqing Chen , Erdinc Saygin