Materials Map

Discover the materials research landscape. Find experts, partners, networks.

  • About
  • Privacy Policy
  • Legal Notice
  • Contact

The Materials Map is an open tool for improving networking and interdisciplinary exchange within materials research. It enables cross-database search for cooperation and network partners and discovering of the research landscape.

The dashboard provides detailed information about the selected scientist, e.g. publications. The dashboard can be filtered and shows the relationship to co-authors in different diagrams. In addition, a link is provided to find contact information.

×

Materials Map under construction

The Materials Map is still under development. In its current state, it is only based on one single data source and, thus, incomplete and contains duplicates. We are working on incorporating new open data sources like ORCID to improve the quality and the timeliness of our data. We will update Materials Map as soon as possible and kindly ask for your patience.

To Graph

1.080 Topics available

To Map

977 Locations available

693.932 PEOPLE
693.932 People People

693.932 People

Show results for 693.932 people that are selected by your search filters.

←

Page 1 of 27758

→
←

Page 1 of 0

→
PeopleLocationsStatistics
Naji, M.
  • 2
  • 13
  • 3
  • 2025
Motta, Antonella
  • 8
  • 52
  • 159
  • 2025
Aletan, Dirar
  • 1
  • 1
  • 0
  • 2025
Mohamed, Tarek
  • 1
  • 7
  • 2
  • 2025
Ertürk, Emre
  • 2
  • 3
  • 0
  • 2025
Taccardi, Nicola
  • 9
  • 81
  • 75
  • 2025
Kononenko, Denys
  • 1
  • 8
  • 2
  • 2025
Petrov, R. H.Madrid
  • 46
  • 125
  • 1k
  • 2025
Alshaaer, MazenBrussels
  • 17
  • 31
  • 172
  • 2025
Bih, L.
  • 15
  • 44
  • 145
  • 2025
Casati, R.
  • 31
  • 86
  • 661
  • 2025
Muller, Hermance
  • 1
  • 11
  • 0
  • 2025
Kočí, JanPrague
  • 28
  • 34
  • 209
  • 2025
Šuljagić, Marija
  • 10
  • 33
  • 43
  • 2025
Kalteremidou, Kalliopi-ArtemiBrussels
  • 14
  • 22
  • 158
  • 2025
Azam, Siraj
  • 1
  • 3
  • 2
  • 2025
Ospanova, Alyiya
  • 1
  • 6
  • 0
  • 2025
Blanpain, Bart
  • 568
  • 653
  • 13k
  • 2025
Ali, M. A.
  • 7
  • 75
  • 187
  • 2025
Popa, V.
  • 5
  • 12
  • 45
  • 2025
Rančić, M.
  • 2
  • 13
  • 0
  • 2025
Ollier, Nadège
  • 28
  • 75
  • 239
  • 2025
Azevedo, Nuno Monteiro
  • 4
  • 8
  • 25
  • 2025
Landes, Michael
  • 1
  • 9
  • 2
  • 2025
Rignanese, Gian-Marco
  • 15
  • 98
  • 805
  • 2025

Baltazart, Vincent

  • Google
  • 6
  • 14
  • 34

in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (6/6 displayed)

  • 2022Optimization and sensitivity analysis of existing deep learning models for pavement surface monitoring using low-quality images6citations
  • 2016Progress in monitoring the debonding within pavement structures during accelerated pavement testing on the Ifsttar's fatigue carouselcitations
  • 2014Data processing of ground-penetrating radar signals for the detection of discontinuities using polarization diversitycitations
  • 2011On variants of the frequency power law for the electromagnetic characterization of hydraulic concrete28citations
  • 2009Effects of Frequency-Dependent Attenuation on the Performance of Time Delay Estimation Techniques Using Ground Penetrating Radarcitations
  • 2009Effects of Frequency-Dependent Attenuation on the Performance of Time Delay Estimation Techniques Using Ground Penetrating Radarcitations

Places of action

Chart of shared publication
Roberts, Ronald
1 / 1 shared
Menant, Fabien
1 / 1 shared
Mino, Gaetano Di
1 / 2 shared
Derobert, Xavier
4 / 18 shared
Bastard, Cédric Le
2 / 2 shared
Simonin, Jean-Michel
1 / 2 shared
Sagnard, Florence
1 / 5 shared
Tarel, Jean Philippe
1 / 1 shared
Tebchrany, Elias
1 / 1 shared
Chahine, Khaled
3 / 3 shared
Ihamouten, Amine
1 / 11 shared
Villain, Géraldine
1 / 34 shared
Wang, Yide
2 / 2 shared
Le Bastard, Cédric
1 / 2 shared
Chart of publication period
2022
2016
2014
2011
2009

Co-Authors (by relevance)

  • Roberts, Ronald
  • Menant, Fabien
  • Mino, Gaetano Di
  • Derobert, Xavier
  • Bastard, Cédric Le
  • Simonin, Jean-Michel
  • Sagnard, Florence
  • Tarel, Jean Philippe
  • Tebchrany, Elias
  • Chahine, Khaled
  • Ihamouten, Amine
  • Villain, Géraldine
  • Wang, Yide
  • Le Bastard, Cédric
OrganizationsLocationPeople

conferencepaper

Data processing of ground-penetrating radar signals for the detection of discontinuities using polarization diversity

  • Baltazart, Vincent
  • Sagnard, Florence
  • Tarel, Jean Philippe
  • Tebchrany, Elias
Abstract

In civil engineering, ground penetrating radar (GPR) is used to survey pavement thickness at traffic speed, detect and localize buried objects (pipes, cables, voids, cavities), zones of cracks and discontinuities in concrete or soils. In this work, a ground-coupled radar made of a pair of transmitting and receiving bowtie-slot antennas is moved linearly on the soil surface to detect the reflected waves induced by discontinuities in the subsurface. The GPR system operates in the frequency domain using a step-frequency continuous wave (SFCW) using a Vector Network Analyzer (VNA) in an ultra-wide band [0.3 ; 4] GHz. The detection of targets is usually focused on time imaging. Thus, the targets (limited in size) are usually shown by diffraction hyperbolas on a Bscan image that is an unfocused depiction of the scatterers. The contrast in permittivity and the ratio between the size of the object and the wavelength are important parameters in the detection process. Thus, we have made a first study on the use of polarization diversity to obtain additional information relative to the contrast between the soil and the target and the dielectric characteristics of a target. The two main polarizations configurations of the radar have been considered in the presence of objects having a pipe geometry: the TM (Transverse Magnetic) and TE (Transverse Electric. To interpret the diffraction hyperbolas on a Bscan image, we have used pre-processing techniques are necessary to reduce the clutter signal which can overlap and obscure the target responses, particularly shallow objects. The clutter, which can be composed of the direct coupling between the antennas and the reflected wave from the soil surface, the scattering on the heterogeneities due to the granular nature of the subsurface material, and some additive noise, varies with soil dielectric characteristics and/or surface roughness and leads to uncertainty in the measurements (additive noise). Because of the statistical nature of the clutter, we have considered and quantified the performance of the Principal Component Analysis (PCA) and the Independent Component Analysis (ICA) in remove or minimizing the clutter using the receiver operating characteristics (ROC) graph. The study has been focused in the preferred polarization on simulated and experimental scenarios of soil structures with a few parameters such as the presence of a different target depths which are capable to perturb the first arrival times made of clutter components, and different dielectric characteristics (conductive or dielectric) of a given target (pipe).

Topics
  • impedance spectroscopy
  • surface
  • crack
  • void