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Multiple-Instance Hidden Markov Model for GPR-Based Landmine Detection

Achut Manandhar, Peter A. Torrione, Leslie M. Collins, Kenneth D. Morton
2015 IEEE Transactions on Geoscience and Remote Sensing  
Hidden Markov models (HMMs) have previously been successfully applied to subsurface threat detection using ground penetrating radar (GPR) data.  ...  However, parameter estimation in most HMM-based landmine detection approaches is difficult since object locations are typically well known for the 2-D coordinates on the Earth's surface but are not well  ...  Army RDECOM CERDEC Night Vision and Electronic Sensors Directorate for providing supporting Grants (W911NF-09-1-0487 and W911NF-06-1-0357) through the Army Research Office and J. Bolton, J.  ... 
doi:10.1109/tgrs.2014.2346954 fatcat:cs2hzovurjgupkvchqqmlkt26y

Landmine detection with Multiple Instance Hidden Markov Models

Seniha Esen Yuksel, Jeremy Bolton, Paul D. Gader
2012 2012 IEEE International Workshop on Machine Learning for Signal Processing  
A novel Multiple Instance Hidden Markov Model (MI-HMM) is introduced for classification of ambiguous time-series data, and its training is accomplished via Metropolis-Hastings sampling.  ...  Experiments on the landmine dataset show that MI-HMM learning is very effective, and outperforms the state-of-the-art models that are currently being used in the field for landmine detection.  ...  In this study, a novel multiple instance hidden Markov model (MI-HMM) that uses MIL for time series data is developed.  ... 
doi:10.1109/mlsp.2012.6349734 dblp:conf/mlsp/YukselBG12 fatcat:5j3mq3cjrrawfo4c3vsxu5bbvy

Ensemble hidden Markov models with application to landmine detection

Anis Hamdi, Hichem Frigui
2015 EURASIP Journal on Advances in Signal Processing  
Our approach was evaluated on a real-world application for landmine detection using ground-penetrating radar (GPR).  ...  We introduce an ensemble learning method for temporal data that uses a mixture of hidden Markov models (HMM).  ...  Baseline HMM classifier for landmine detection The baseline HMM classifier for GPR-based landmine detection was first introduced in [5] .  ... 
doi:10.1186/s13634-015-0260-8 fatcat:ewllgn5lkbdv7l4x35btytlage

Random set framework for multiple instance learning

Jeremy Bolton, Paul Gader, Hichem Frigui, Pete Torrione
2011 Information Sciences  
Simultaneous Feature and HMM Model Learning for Landmine Detection using Ground Penetrating Radar Hidden Markov Models (HMMs) have been widely used in landmine detection with Ground Penetrating Radar (  ...  Imagery • Cross Entropy Optimization of the Random Set Framework for Multiple ?Instance Learning • Simultaneous Feature and HMM Model Learning for Landmine Detection using Ground ?  ... 
doi:10.1016/j.ins.2010.12.020 fatcat:vfsnlmgmrbhlpaue5evcj35kf4

Real-Time Landmine Detection with Ground-Penetrating Radar Using Discriminative and Adaptive Hidden Markov Models

Hichem Frigui, K. C. Ho, Paul Gader
2005 EURASIP Journal on Advances in Signal Processing  
We propose a real-time software system for landmine detection using ground-penetrating radar (GPR).  ...  The system includes an efficient and adaptive preprocessing component; a hidden Markov model-(HMM-) based detector; a corrective training component; and an incremental update of the background model.  ...  Pete Howard for their support of this research. We also thank the reviewers for their constructive comments.  ... 
doi:10.1155/asp.2005.1867 fatcat:zqsiajicbfagbaqfoyrhvmslay

Multi-perspective high range resolution profiles of landmines

Lauren Wright, Alessio Balleri, Hugh Griffiths, Federico Lombardi
2015 2015 IEEE Radar Conference  
Landmine signatures are expected to present features that are less sensitive to the angle of illumination with respect to those of common cluttered objects, and this can lead to an improvement in detection  ...  The development of low-cost, smaller, faster and lighter Ground Penetrating Radars (GPR), which can be mounted on unmanned platforms, will allow faster and safer 24/7 operations.  ...  ACKNOWLEDGMENT The authors thank the Ammunition Hall at the Defence Academy of the United Kingdom for providing the landmines used for the measurements.  ... 
doi:10.1109/radarconf.2015.7411853 fatcat:kojcr4edqfhljgs6fsd6bfhzvm

UAV Tomographic Synthetic Aperture Radar for Landmine Detection

M. Almutiry
2020 Zenodo  
In this paper, imaging the underground for detecting landmine using TSAR is proposed. The TSAR has the capability of prosing the data in discrete mode regardless of the altitude of UAV's radar.  ...  Anti-personnel landmines deployed by militia groups in conflict zones are a life threat for civilians and need cautious handling while removing.  ...  However, like metal detectors, GPR can trigger false alarms due to the presence of irregularities in the soil, for instance, rocks and roots, when hidden Markov models were used to classify the background  ... 
doi:10.5281/zenodo.4016149 fatcat:og4ttfkyizfozmxsrztin3kvne

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  
Most currently fielded GPR-based landmine detection algorithms utilize feature extraction and statistical learning to develop robust classifiers capable of discriminating buried threats from inert subsurface  ...  be successfully applied to target detection in GPR data.  ...  Frigui for several important suggestions and the anonymous reviewers for their insightful comments.  ... 
doi:10.1109/tgrs.2013.2252016 fatcat:enykrxyjufd4nliqjfs6dpc7rm

Adaptive Multimodality Sensing of Landmines

Lihan He, Shihao Ji, Waymond R. Scott, Lawrence Carin
2007 IEEE Transactions on Geoscience and Remote Sensing  
The problem of adaptive multi-modality sensing of landmines is considered, based on electromagnetic induction (EMI) and ground-penetrating radar (GPR) sensors.  ...  Two formulations are considered, based on a partially observable Markov decision process (POMDP) framework.  ...  The data are assumed to be represented by a hidden Markov model (HMM) with two sets of observations, as shown in Fig. 4(b) .  ... 
doi:10.1109/tgrs.2007.894933 fatcat:4qlujos4pvb3jlljtnmvf3nw4y

2015 Index IEEE Transactions on Geoscience and Remote Sensing Vol. 53

2015 IEEE Transactions on Geoscience and Remote Sensing  
., +, TGRS May 2015 2640-2651 Multiple-Instance Hidden Markov Model for GPR-Based Landmine Detection.  ...  ., +, TGRS April 2015 1842- 1854 Hidden Markov models Multiple-Instance Hidden Markov Model for GPR-Based Landmine Detec- tion.  ... 
doi:10.1109/tgrs.2015.2513444 fatcat:zuklkpk4gjdxjegoym5oagotzq

Multi-stream continuous hidden Markov models with application to landmine detection

Oualid Missaoui, Hichem Frigui, Paul Gader
2013 EURASIP Journal on Advances in Signal Processing  
We propose a multi-stream continuous hidden Markov model (MSCHMM) framework that can learn from multiple modalities.  ...  We also apply them to the problem of landmine detection using ground penetrating radar.  ...  Introduction Hidden Markov models (HMMs) have emerged as a powerful paradigm for modeling stochastic processes and pattern sequences.  ... 
doi:10.1186/1687-6180-2013-40 fatcat:saury3tverd43p7bh25tzhxhjm

Robust adaptive detection of buried pipes using GPR

Q. Hoarau, G. Ginolhac, A.M. Atto, J.M. Nicolas
2017 Signal Processing  
Detection of buried objects such as pipes using a Ground Penetrating Radar (GPR) is intricate for three main reasons.  ...  For this detector, noise is assumed to follow a Spherically Invariant Random Vector (SIRV) distribution in order to obtain a robust detection.  ...  Acknowledgment We thank the ENGIE Company for providing GPR datasets and BPI France for funding this work. Also, we are grateful Sophie Reed for correcting English mistakes in this paper.  ... 
doi:10.1016/j.sigpro.2016.07.001 fatcat:bpvch2ld55astprz5kvqpiab5a

Robust adaptive detection of buried pipes using GPR

Q. Hoarau, G. Ginolhac, A. M. Atto, J. M. Nicolas, J. P. Ovarlez
2016 2016 24th European Signal Processing Conference (EUSIPCO)  
Detection of buried objects such as pipes using a Ground Penetrating Radar (GPR) is intricate for three main reasons.  ...  For this detector, noise is assumed to follow a Spherically Invariant Random Vector (SIRV) distribution in order to obtain a robust detection.  ...  Acknowledgment We thank the ENGIE Company for providing GPR datasets and BPI France for funding this work. Also, we are grateful Sophie Reed for correcting English mistakes in this paper.  ... 
doi:10.1109/eusipco.2016.7760305 dblp:conf/eusipco/HoarauGANO16 fatcat:w7aeoatdlvd3rizgtuh4sitlke

2012 Index IEEE Transactions on Geoscience and Remote Sensing Vol. 50

2012 IEEE Transactions on Geoscience and Remote Sensing  
., +, TGRS May 2012 1881-1896 Hidden Markov models Auroral Sequence Representation and Classification Using Hidden Markov Models.  ...  ., +, TGRS Nov. 2012 4301-4312 Mixture Model for Multiple Instance Regression and Applications in Re- mote Sensing.  ...  Radar resolution A Novel Method for Imaging of Group Targets Moving in a Formation. Bai, X., +, TGRS Jan. 2012  ... 
doi:10.1109/tgrs.2012.2229656 fatcat:hjrotpfsqzhxlnnme27ftv33cu

A Review of GPR Application on Transport Infrastructures: Troubleshooting and Best Practices

Mercedes Solla, Vega Pérez-Gracia, Simona Fontul
2021 Remote Sensing  
Ground penetrating radar (GPR) is one of the most recommended non-destructive methods for routine subsurface inspections.  ...  The non-destructive testing and diagnosis of transport infrastructures is essential because of the need to protect these facilities for mobility, and for economic and social development.  ...  Universidade de Vigo (Spain), the Geophysics and Earthquake Engineering (GIES) research group of the Universitat Politècnica de Catalunya (Spain), and the Transport Department of the National Laboratory for  ... 
doi:10.3390/rs13040672 fatcat:casg4w4nkjfkzbpb6bqk7ou7k4
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