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Front Matter: Volume 9823

Proceedings of SPIE, Steven S. Bishop, Jason C. Isaacs
2016 Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XXI  
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

Proceedings of SPIE, Steven S. Bishop, Jason C. Isaacs
2015 Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XX  
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  
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

M. Mostafa, Fathy Ahmed, Aly Attallah
2017 International Conference on Aerospace Sciences and Aviation Technology  
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

Jason C. Isaacs, Steven S. Bishop
2018 Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XXIII  
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

Peter A. Torrione, Kenneth D. Morton, Rayn Sakaguchi, Leslie M. Collins
2014 IEEE Transactions on Geoscience and Remote Sensing  
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

Xavier Núñez-Nieto, Mercedes Solla, Paula Gómez-Pérez, Henrique Lorenzo
2014 Remote Sensing  
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

Federico Lombardi, Hugh D. Griffiths, Alessio Balleri, Maurizio Lualdi
2017 2017 9th International Workshop on Advanced Ground Penetrating Radar (IWAGPR)  
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

Silvia Lameri, Federico Lombardi, Paolo Bestagini, Maurizio Lualdi, Stefano Tubaro
2017 2017 25th European Signal Processing Conference (EUSIPCO)  
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

Seniha E. Yuksel, Gozde Bozdagi Akar, Serhat Ozturk, Steven S. Bishop, Jason C. Isaacs
2015 Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XX  
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

Paolo Bestagini, Silvia Lameri, Federico Lombardi, Maurizio Lualdi, Stefano Tubaro
2018 Zenodo  
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

Proceedings of SPIE, Russell S. Harmon, John H. Holloway, Jr., J. Thomas Broach
2011 Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XVI  
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

Federico Lombardi, Hugh D. Griffiths, Alessio Balleri
2018 2018 IEEE Radar Conference (RadarConf18)  
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

Prabhat Sharma, Bambam Kumar, Dharmendra Singh
2018 Defence Science Journal  
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]

Daniël Reichman, Leslie M. Collins, Jordan M. Malof
2016 arXiv   pre-print
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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