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scientifique

Application of convolutional and recurrent neural networks for buried threat detection using ground penetrating radar data / Mahdi Moalla in IEEE Transactions on geoscience and remote sensing, vol 58 n° 10 (October 2020)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 58 n° 10 (October 2020) . - pp 7022 - 7034 Titre : Application of convolutional and recurrent neural networks for buried threat detection using ground penetrating radar data Type de document : Article/Communication Auteurs : Mahdi Moalla, Auteur ; Hichem Frigui, Auteur ; Andrew Karem, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 7022 - 7034 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] cible cachée [Termes IGN] classification barycentrique [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] détection d'objet [Termes IGN] données radar [Termes IGN] image radar moirée [Termes IGN] mine antipersonnel [Termes IGN] radar pénétrant GPR [Termes IGN] réseau neuronal récurrent [Termes IGN] sous-sol Résumé : (auteur) We propose discrimination algorithms for buried threat detection (BTD) that exploit deep convolutional neural networks (CNNs) and recurrent neural networks (RNN) to analyze 2-D GPR B-scans in the down-track (DT) and cross-track (CT) directions as well as 3-D GPR volumes. Instead of imposing a specific model or handcrafted features, as in most existing detectors, we use large real GPR data collections and data-driven approaches that learn: 1) features characterizing buried explosive objects (BEOs) in 2-D B-scans, both in the DT and CT directions; 2) the variation of the CNN features learned in a fixed 2-D view across the third dimension; and 3) features characterizing BEOs in the original 3-D space. The proposed algorithms were trained and evaluated using large experimental GPR data covering a surface area of 120 000 m 2 from 13 different lanes across two U.S. test sites. These data include a diverse set of BEOs consisting of varying shapes, metal content, and underground burial depths. We provide some qualitative analysis of the proposed algorithms by visually comparing their performance and consistency along different dimensions and visualizing typical features learned by some nodes of the network. We also provide quantitative analysis that compares the receiver operating characteristics (ROCs) obtained using the proposed algorithms with those obtained using existing approaches based on CNN as well as traditional learning. Numéro de notice : A2020-586 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2020.2978763 Date de publication en ligne : 25/03/2020 En ligne : https://doi.org/10.1109/TGRS.2020.2978763 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95914 [article]

Cartographic symbols for humanitarian demining / J. Kostelnick in Cartographic journal (the), vol 45 n° 1 (February 2008)  

Public [article]  inCartographic journal (the) > vol 45 n° 1 (February 2008) . - pp 18 - 31 Titre : Cartographic symbols for humanitarian demining Type de document : Article/Communication Auteurs : J. Kostelnick, Auteur ; J. Dobson, Auteur ; S. Egbert, Auteur ; M.D. Dunbar, Auteur Année de publication : 2008 Article en page(s) : pp 18 - 31 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Cartographie thématique [Termes IGN] carte thématique [Termes IGN] mine antipersonnel [Termes IGN] normalisation [Termes IGN] symbole graphique Résumé : (Auteur) A new standard set of cartographic symbols for landmine hazards and mine actions (e.g., clearances, hazard reductions, mine risk education (MRE), and technical surveys) in humanitarian demining activities is proposed, as well as a five-step approach that was utilised to develop the symbol set and that may be applied to the design of related map symbols in digital mapping environments. To promulgate the new symbol set, the Geneva International Centre for Humanitarian Demining and the American Geographical Society recently sponsored workshops in New York, NY, and Reston, VA. Workshop attendees, including key representatives from international organisations, private firms, and NGOs, indicated great enthusiasm for a future global standard. Copyright British Cartographic Society Numéro de notice : A2008-131 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1179/000870408X276585 En ligne : https://doi.org/10.1179/000870408X276585 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29126 [article]

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Code-barres	Cote	Support	Localisation	Section	Disponibilité
030-08011	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Optimal manoeuvring of seismic sensors for localization of subsurface targets / Mubashir Alam in IEEE Transactions on geoscience and remote sensing, vol 45 n° 5 Tome 1 (May 2007)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 45 n° 5 Tome 1 (May 2007) . - pp 1247 - 1257 Titre : Optimal manoeuvring of seismic sensors for localization of subsurface targets Type de document : Article/Communication Auteurs : Mubashir Alam, Auteur ; Volkan Cevher, Auteur ; et al., Auteur Année de publication : 2007 Article en page(s) : pp 1247 - 1257 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes IGN] cible cachée [Termes IGN] géopositionnement [Termes IGN] mine [Termes IGN] mine antipersonnel [Termes IGN] onde sismique [Termes IGN] radar pénétrant GPR Résumé : (Auteur) We consider the problem of detecting and locating subsurface objects by using a maneuvering array that receives scattered seismic surface waves. We demonstrate an adaptive system that moves an array of receivers according to an optimal positioning algorithm that is based on the theory of optimal experiments. The goal is to minimize the number of distinct measurements (array movements) needed to localize objects such as buried landmines. The adaptive localization algorithm has been tested using data collected in a laboratory facility. The performance of the algorithm is exhibited for cases with one or two targets and in the presence of common types of clutter such as rocks in the soil. Results are also shown for a case where the propagation properties of the medium vary spatially. In these tests, the landmines were located using three or four array movements. It is envisioned that future systems could incorporate this new method into a portable mobile mine-location system. Copyright IEEE Numéro de notice : A2007-293 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2007.894551 En ligne : https://doi.org/10.1109/TGRS.2007.894551 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28656 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
065-07051A	RAB	Revue	Centre de documentation	En réserve L003	Disponible

A review of satellite and airborne sensors for remote sensing based detection of minefields and landmines / B.H. Maathuis in International Journal of Remote Sensing IJRS, vol 25 n° 23 (December 2004)  

Public [article]  inInternational Journal of Remote Sensing IJRS > vol 25 n° 23 (December 2004) . - pp 5201 - 5245 Titre : A review of satellite and airborne sensors for remote sensing based detection of minefields and landmines Type de document : Article/Communication Auteurs : B.H. Maathuis, Auteur ; John L. Van Genderen, Auteur Année de publication : 2004 Article en page(s) : pp 5201 - 5245 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] capteur aérien [Termes IGN] capteur spatial [Termes IGN] chambre DTC [Termes IGN] image Landsat-ETM+ [Termes IGN] Landsat [Termes IGN] longueur d'onde [Termes IGN] mine antipersonnel [Termes IGN] rayonnement proche infrarouge [Termes IGN] SPOT Résumé : (Auteur) This paper focuses on the use of space and airborne sensors that can be applied to detect landmines and minefields. First the landmine and minefield problem is addressed and examples of the use of remote sensing images are presented that could provide valuable information for the mine action process and assist in conventional minefield and landmine detection methods. This is followed by an overview on relevant (declassified) aspects related to strategic overhead detection techniques developed by the military/intelligence community as well as those of civilian space and airborne remote sensing programmes. The airborne sensing techniques describe the state of the art of sensors such as optical (film, multi- and hyperspectral sensors), thermal infrared as well as microwave sensors and their suitability-limitations for remote sensing based minefield and landmine detection purposes. Numéro de notice : A2004-468 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160412331270803 En ligne : https://doi.org/10.1080/01431160412331270803 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=26988 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
080-04211	RAB	Revue	Centre de documentation	En réserve L003	Exclu du prêt

Detection of buried targets via active selection of labeled data: Application to sensing subsurface UXO / Y. Zhang in IEEE Transactions on geoscience and remote sensing, vol 42 n° 11 (November 2004)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 42 n° 11 (November 2004) . - pp 2535 - 2543 Titre : Detection of buried targets via active selection of labeled data: Application to sensing subsurface UXO Type de document : Article/Communication Auteurs : Y. Zhang, Auteur ; X. Liao, Auteur ; L. Carin, Auteur Année de publication : 2004 Article en page(s) : pp 2535 - 2543 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes IGN] cible cachée [Termes IGN] classification [Termes IGN] détection de cible [Termes IGN] erreur moyenne quadratique [Termes IGN] matrice [Termes IGN] matrice d'information de Fischer [Termes IGN] mine antipersonnel [Termes IGN] signature spectrale Résumé : (Auteur) When sensing subsurface targets, such as land-mine and unexploded ordnance (UXO), the target signatures are typically a strong function of environmental and historical circumstances. Consequently, it is difficult to constitute a universal training set for design of detection or classification algorithms. In this paper, we develop an efficient procedure by which information-theoretic concepts are used to design the basis functions and training set, directly from the site-specific measured data specifically, assume that measured data (e.g., induction and/or magnetometer) are available from a given site, unlabeled in the sense that it is not known a priori whether a given signature is associated with a target or clutter. For N signatures, the data may be expressed as {Xi, Yi}i=1,N, where xi is the measured data or buried object i, and yi is the associated unknown binary label (target/nontarget). Let the N xi define the set X. The algorithm works in four steps : 1) the Fisher information matrix is used to select a set of basis functions for the kernel-based algorithm, this step defining a set of n signatures Bn X that are most informative in characterizing the signature distribution of the site; 2) the Fisher information matrix is used again to define a small subset Xs X, composed of those xi for which knowledge of the associated labels yi would be most informative in defining the weights, for the basis functions in Bn ; 3) the buried objects associated with the signatures in Xs., are excavated, yielding the associated labels yi, represented by the set Ys.; and 4) using Bn, Xs, and Ys, a kernel-based classifier is designed for use in classifying all remaining buried objects. This framework is discussed in detail, with example results presented for an actual buried-UXO site. Numéro de notice : A2004-462 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2004.836270 En ligne : https://doi.org/10.1109/TGRS.2004.836270 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=26982 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
065-04111	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Ground penetrating radar, 2nd edition / D.J. Daniels (2004)

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