Learning-by-examples techniques as applied to electromagnetics

A Massa, G Oliveri, M Salucci, N Anselmi… - Journal of …, 2018 - Taylor & Francis
There is a wide number of problems in electromagnetic (EM) engineering that require a real-
time response or in which the input–output relationship is not a-priori known or cannot be …

Automatic recognition of tunnel lining elements from GPR images using deep convolutional networks with data augmentation

H Qin, D Zhang, Y Tang, Y Wang - Automation in Construction, 2021 - Elsevier
Tunnel lining inspection using ground penetrating radar (GPR) is a routine procedure to
ensure construction quality. Yet, the interpretation of GPR data relies heavily on manual …

Review of artificial intelligence applications for virtual sensing of underground utilities

KS Oguntoye, S Laflamme, R Sturgill, DJ Eisenmann - Sensors, 2023 - mdpi.com
Accurately identifying the location and depth of buried utility assets became a considerable
challenge in the construction industry, for which accidental strikes can cause important …

[HTML][HTML] Seamless mapping of long-term (2010–2020) daily global XCO and XCH from the Greenhouse Gases Observing Satellite (GOSAT), Orbiting Carbon …

Y Wang, Q Yuan, T Li, Y Yang, S Zhou… - Earth System Science …, 2023 - essd.copernicus.org
Precise and continuous monitoring of long-term carbon dioxide (CO 2) and methane (CH 4)
over the globe is of great importance, which can help study global warming and achieve the …

Radarcat: Radar categorization for input & interaction

HS Yeo, G Flamich, P Schrempf, D Harris-Birtill… - Proceedings of the 29th …, 2016 - dl.acm.org
In RadarCat we present a small, versatile radar-based system for material and object
classification which enables new forms of everyday proximate interaction with digital …

GPR B scan image analysis with deep learning methods

U Ozkaya, F Melgani, MB Bejiga, L Seyfi, M Donelli - Measurement, 2020 - Elsevier
In this paper, we propose a Convolutional Support Vector Machine (CSVM) network for the
analysis of Ground Penetrating Radar B Scan (GPR B Scan) images. Similar to a …

In-situ recognition of moisture damage in bridge deck asphalt pavement with time-frequency features of GPR signal

J Zhang, C Zhang, Y Lu, T Zheng, Z Dong… - … and Building Materials, 2020 - Elsevier
A complete solution, including an effective non-destructive evaluation (NDE) method and an
automatic recognition model, was provided for the rapid diagnosis of moisture damage in …

GPR signature detection and decomposition for mapping buried utilities with complex spatial configuration

C Yuan, S Li, H Cai, VR Kamat - Journal of Computing in Civil …, 2018 - ascelibrary.org
The information of exact locations of underground utilities is an essential piece of evidence
for preventing utility strikes in excavation work. Ground penetrating radar (GPR), which has …

Performance assessment of SVM-based classification techniques for the detection of artificial debondings within pavement structures from stepped-frequency A-scan …

SS Todkar, C Le Bastard, V Baltazart, A Ihamouten… - NDT & E …, 2019 - Elsevier
Owing to traffic and weather conditions, pavement structures may suffer from horizontal and
vertical cracks that shorten the overall lifetime of roadways. In this paper, we focus on the …

The noise attenuation and stochastic clutter removal of ground penetrating radar based on the K-SVD dictionary learning

D Feng, S Liu, J Yang, X Wang, X Wang - IEEE Access, 2021 - ieeexplore.ieee.org
The ground penetrating radar (GPR) data in the complex detection environment is non-
stationary, non-Gaussian, and non-uniform, so the traditional noise attenuation methods are …