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Front Matter: Volume 9823
2016
Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XXI
Preserved Fulltext
SPIE uses a six-digit CID article numbering system in which: The first four digits correspond to the SPIE volume number. The last two digits indicate publication order within the volume using a Base ...
Publication of record for individual papers is online in the SPIE Digital Library. ...
detecting novel buried threats with ground-
penetrating radar [9823-46]
9823 1A
Algorithm development for deeply buried threat detection in GPR data [9823-47]
9823 1B
Enhancements to GPR buried UXO ...
doi:10.1117/12.2244407
fatcat:nqor2f5awfbe7pa5jk6bof2lba
Front Matter: Volume 9454
2015
Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XX
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SPIE uses a six-digit CID article numbering system in which: The first four digits correspond to the SPIE volume number. ...
The papers included in this volume were part of the technical conference cited on the cover and title page. Papers were selected and subject to review by the editors and conference program committee. ...
[9454-25]
SESSION 7
EO/IR TECHNOLOGIES AND SIGNAL PROCESSING III
9454 0Q
Multi-scale HOG prescreening algorithm for detection of buried explosive hazards in FL-IR
and FL-GPR data [9454-26]
9454 ...
doi:10.1117/12.2184320
fatcat:oqq2mxlilvgopnbiwe5away4xe
Front Matter: Volume 10182
2017
Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XXII
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Publication of record for individual papers is online in the SPIE Digital Library. SPIEDigitalLibrary.org Paper Numbering: Proceedings of SPIE follow an e-First publication model. ...
Utilization of CIDs allows articles to be fully citable as soon as they are published online, and connects the same identifier to all online and print versions of the publication. ...
Contents
DOWN-LOOKING GPR TECHNOLOGIES I
0T Using data compression for buried hazard detection 10182 0U Improvements to the Histogram of Oriented Gradient (HOG) prescreener for buried threat detection ...
doi:10.1117/12.2280588
fatcat:rbdty44k75av7puyuk332nrmhe
Modern Signal Processing Techniques for GPR Applications
2017
International Conference on Aerospace Sciences and Aviation Technology
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This paper introduces a survey of different modern signal processing techniques used in the ground penetrating radar (GPR) for an ongoing research regarding buried objects detection. ...
In GPR, microwaves signals are transmitted until an object reflects them back, then the reflected signals are processed in order to extract information about the target. ...
The objective is to detect, locate and identify a buried object in GPR image. ...
doi:10.21608/asat.2017.22383
fatcat:vyamts2mbrd7feafpr4v7fmk54
Front Matter: Volume 10628
2018
Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XXIII
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Publication of record for individual papers is online in the SPIE Digital Library. SPIEDigitalLibrary.org Paper Numbering: Proceedings of SPIE follow an e-First publication model. ...
Utilization of CIDs allows articles to be fully citable as soon as they are published online, and connects the same identifier to all online and print versions of the publication. ...
Improving supervised learning algorithms for threat detection in ground penetrating radar data 10628 0G Comparison of several single and multiple instance learning methods for detecting buried explosive ...
doi:10.1117/12.2322389
fatcat:iqktcmbwhngrjcdqs33tsspf2e
Histograms of Oriented Gradients for Landmine Detection in Ground-Penetrating Radar Data
2014
IEEE Transactions on Geoscience and Remote Sensing
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be successfully applied to target detection in GPR data. ...
This paper explores the relationship between and application of one modern computer vision feature extraction technique, namely histogram of oriented gradients (HOG), to landmine detection in GPR data. ...
ACKNOWLEDGMENT The authors would like to thank Dr. H. Frigui for several important suggestions and the anonymous reviewers for their insightful comments. ...
doi:10.1109/tgrs.2013.2252016
fatcat:enykrxyjufd4nliqjfs6dpc7rm
GPR Signal Characterization for Automated Landmine and UXO Detection Based on Machine Learning Techniques
2014
Remote Sensing
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This study evaluates the effectiveness of ground penetrating radar (GPR) in demining and unexploded ordnance detection using 2.3-GHz and 1-GHz high-frequency antennas. ...
An automated detection tool based on machine learning techniques is also presented with the aim of automatically detecting underground explosive artifacts. ...
Author Contributions All authors contributed extensively to the work presented in the manuscript.
Conflicts of Interest The authors declare no conflict of interest. ...
doi:10.3390/rs6109729
fatcat:vkrpvr7fdnarnpgkv2dub6c76q
Preliminary results on multi offset GPR for imaging of landmines
2017
2017 9th International Workshop on Advanced Ground Penetrating Radar (IWAGPR)
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This paper analyses a set of experimental data collected in a recent multi-offset GPR measurement campaign with inert landmines composed of different assemblies buried in sandy soil. ...
Ground Penetrating Radar (GPR) is widely recognised as an operationally useful sensor for mine detection as it can offer better detection performance than the ubiquitous metal detector in the presence ...
Francesco Fioranelli for assisting during the experimental campaign. We thank IDS Georadar srl for the provision of the GPR equipment. ...
doi:10.1109/iwagpr.2017.7996090
fatcat:ryc3pge5brfl7iyi3ndnva46ee
Landmine detection from GPR data using convolutional neural networks
2017
2017 25th European Signal Processing Conference (EUSIPCO)
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The presence of buried landmines is a serious threat in many areas around the World. ...
Despite various techniques have been proposed in the literature to detect and recognize buried objects, automatic and easy to use systems providing accurate performance are still under research. ...
In this work we address the task of buried object detection in GPR data. ...
doi:10.23919/eusipco.2017.8081259
dblp:conf/eusipco/LameriLBLT17
fatcat:ya6ua56qkzdkxpszlow5gec6b4
Fusion of forward-looking infrared camera and down-looking ground penetrating radar for buried target detection
2015
Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XX
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In this paper, we propose a system to detect buried disk-shaped landmines from ground penetrating radar (GPR) and forward-looking long wave infrared (FL-LWIR) data. ...
Then possible target regions are further analyzed using the GPR data. IR data processing is done in three steps such as preprocessing, target detection, and postprocessing. ...
This GPR data was first processed using the common techniques as described and used in [1]- [6] . ...
doi:10.1117/12.2176735
fatcat:3r6puzjnpzg3dmeu5mstxsedzi
Landmine Detection From Gpr Data Using Convolutional Neural Networks
2018
Zenodo
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Publication in the conference proceedings of EUSIPCO, Kos island, Greece, 2017 ...
In this work we address the task of buried object detection in GPR data. ...
In the literature many GPR signal and image processing techniques have been proposed for the automated detection of buried objects. ...
doi:10.5281/zenodo.1159844
fatcat:uq2enqvl6bedpb6rdrcdxf5nqu
Front Matter: Volume 8017
2011
Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XVI
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Numbers in the index correspond to the last two digits of the six-digit CID number. ...
SPIE uses a six-digit CID article numbering system in which: The first four digits correspond to the SPIE volume number. ...
in GPR data [8017-53] P. ...
doi:10.1117/12.901333
fatcat:or7o7x22evbztnod4mkgiamsee
Landmine internal structure detection from ground penetrating radar images
2018
2018 IEEE Radar Conference (RadarConf18)
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Due to its ability of detecting both metallic and non-metallic objects, ground penetrating radar (GPR) is a promising method for detecting landmines that may allow faster and safer operations. ...
This study demonstrates that from a set of high resolution GPR slices the internal design of the landmine can be properly imaged and characterised, confirming the applicability of the methodology and the ...
We are also grateful to A. Sarri and A. Del Moro from IDS for their support and help in the field experiments. ...
doi:10.1109/radar.2018.8378733
fatcat:6hfgsup4pfcrzls3nnwofr27fu
Development of Adaptive Threshold and Data Smoothening Algorithm for GPR Imaging
2018
Defence Science Journal
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The blind threshold was decided to use normal random variable variance and image data variance. Further, the image was smoothened by random variance ratio to image data variance. ...
There are many approaches available to separate the background and foreground in image processing applications. ...
Nabelek 16 , et al. used non-negative matrix factorisation (NMF) in GPR to improve the detection of deeply buried non-metal objects. ...
doi:10.14429/dsj.68.12354
fatcat:4qclsydhfjc57gtzbpbqxfbti4
On Choosing Training and Testing Data for Supervised Algorithms in Ground Penetrating Radar Data for Buried Threat Detection
[article]
2016
arXiv
pre-print
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Training data most often consists of 2-dimensional images (or patches) of GPR data, from which features are extracted, and provided to the classifier during training and testing. ...
Ground penetrating radar (GPR) is one of the most popular and successful sensing modalities that has been investigated for landmine and subsurface threat detection. ...
INTRODUCTION A popular approach for detecting buried threats, such as landmines and other explosive hazards, is the use of remote sensing technologies. ...
arXiv:1612.03477v1
fatcat:tsvvvajycfapbgaw2stzq2weeu
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