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Transfer Learning Enhanced Full Waveform Inversion* [PDF]
2023 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM), 2023 We propose a way to favorably employ neural networks in the field of non-destructive testing using Full Waveform Inversion (FWI). The presented methodology discretizes the unknown material distribution in the domain with a neural network within an adjoint optimization.
Stefan Kollmannsberger +2 more
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DECOMPOSITION TECHNIQUES FOR ICESAT/GLAS FULL-WAVEFORM DATA [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2018 The geoscience laser altimeter system (GLAS) on the board Ice, Cloud, and land Elevation Satellite (ICESat), is the first long-duration space borne full-waveform LiDAR for measuring the topography of the ice shelf and temporal variation, cloud and ...
Z. Liu, X. Gao, G. Li, J. Chen
doaj +2 more sources
Accelerated Full Waveform Inversion by Deep Compressed Learning [PDF]
SensorsWe propose and test a method to reduce the dimensionality of Full Waveform Inversion (FWI) inputs as a computational cost mitigation approach. Given modern seismic acquisition systems, the data (as an input for FWI) required for an industrial-strength ...
Maayan Gelboim +2 more
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Gaussian decomposition method for full waveform data of LiDAR base on neural network [PDF]
Scientific ReportsThe full waveform data from airborne LiDAR (Light Detection and Ranging) provides information on the distance of the target. Accurately extracting the ranging information from the full waveform data is crucial for generating point clouds.
Jie Liu +4 more
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iForest - Biogeosciences and Forestry, 2011 The goal of this review is to present leading examples of current methodologies for extracting forest characteristics from full-waveform LiDAR data. Four key questions are addressed: (i) does full-waveform LiDAR provide advantages over discrete-return ...
Pirotti F
doaj +3 more sources
USING FULL WAVEFORM DATA IN URBAN AREAS [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2013 In this paper, the use of waveform data in urban areas is studied. Full waveform is generally used in non-urban areas, where it can provide better vertical structure description of vegetation compared to discrete return systems.
B. Molnar, S. Laky, C. Toth
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FWNet: Semantic Segmentation for Full-Waveform LiDAR Data Using Deep Learning [PDF]
Sensors, 2020 In the computer vision field, many 3D deep learning models that directly manage 3D point clouds (proposed after PointNet) have been published. Moreover, deep learning-based-techniques have demonstrated state-of-the-art performance for supervised learning
Takayuki Shinohara +2 more
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Full-waveform inversion imaging of the human brain [PDF]
npj Digital Medicine, 2020 Magnetic resonance imaging and X-ray computed tomography provide the two principal methods available for imaging the brain at high spatial resolution, but these methods are not easily portable and cannot be applied safely to all patients.
Lluís Guasch +4 more
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Full waveform inversion for arterial viscoelasticity. [PDF]
Phys Med Biol, 2023 Abstract Objective . Arterial viscosity is emerging as an important biomarker, in addition to the widely used arterial elasticity. This paper presents an approach to estimate arterial viscoelasticity using shear wave elastography (SWE). Approach .
Roy T, Guddati MN.
europepmc +3 more sources
Nonparametric methods for full-waveform ladar images
2012 IEEE Statistical Signal Processing Workshop (SSP), 2012 In the paper, the feasibility of using nonparametric methods to estimate the statistical distributions of full-waveform “Flash” laser radar (ladar) data is demonstrated. Unlike point cloud data, which consists solely of peak range and peak intensity information, full-waveform data captures the entire reflected ladar pulse, which enables more precise ...
Eric A. Buschelman, Richard K. Martin
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