This paper presents a pioneering study in the application of real-time surface landmine detection using a combination of robotics and deep learning. We introduce a novel system integrated within a demining robot, capable of detecting landmines in rea...
Recent advances in unmanned-aerial-vehicle- (UAV-) based remote sensing utilizing lightweight multispectral and thermal infrared sensors allow for rapid wide-area landmine contamination detection and mapping surveys. We present results of a study foc...
Landmines and explosive remnants of war pose a global humanitarian problem and cause numerous casualties long after the conflict has ended. The current approaches for locating landmines, such as metal detection, which require one’s physical pre...
The detection and classification of scatterable landmines present a significant challenge for humanitarian demining, particularly in resource-constrained regions. This paper evaluates the use of a deep learning-based strategy using RGB imagery and th...
This study presents an unmanned aerial vehicle (UAV)-borne vector magnetometer (MAG) system and proposes a new data-processing technique for modeling the residual magnetic anomalies of three types of landmines: the metallic antitank M15, the metallic...
During the armed conflict in Colombia, homemade improvised antipersonnel landmines were used to neutralize the adversary. Many active artifacts remain buried, causing damage to biodiversity by exploding. The extensive literature describes the effects...
An automatic detection methodology for “legbreaker” Antipersonnel Landmines (APL) was developed based on digital image processing techniques and pattern recognition, applied to thermal images acquired by means of an Unmanned Aerial Vehicl...
Landmines and explosive remnants of war are still present in the Western Balkans and remain a deadly legacy of the hostilities at the end of the 20th century. Over the years, several incidents have occurred in Bosnia and Herzegovina, in Serbia, and i...
Dual mode detectors combining metal detection and ground-penetrating radar are increasingly being used during humanitarian demining operations because of their ability to discriminate metal clutter. There are many reports in the academic literature s...
Anti-tank landmines endanger post-conflict recovery. Detecting camouflaged TM-62 landmines in low-altitude unmanned aerial vehicle (UAV) imagery is challenging because targets occupy few pixels and are low-contrast and often occluded. We introduce a...
We modeled and implemented a joint airborne system integrating ground penetrating radar (GPR) and magnetometer (MAG) models specifically for landmine detection applications. We conducted both simulations and experimental analyses of the joint airborn...
Prodders are widely used devices in landmine detection. A sensorized prodder has been developed to detect shallow buried landmines by their vibrational characteristics. However, the influencing mechanisms of prodder’s components on the measured vibra...
Landmine contamination is a significant problem that has devastating consequences worldwide. Unmanned aerial vehicles (UAVs) can play an important role in solving this problem. The technology has the potential to expedite, simplify, and improve the s...
Landmine victims require an engaging and immersive rehabilitation process to maintain motivation and therapeutic adherence, such as virtual reality games. This paper proposes a virtual reality exercise game called Exogames, which works with Nukawa, a...
Commonly found landmines, such as the TM-62M, MON-100, and PDM-1, in the recent Russia–Ukraine war confirm the continued use of metals in munitions. Traditional demining techniques, primarily relying on handheld metal detectors and Ground Penet...
The landmine press is a reliable and valid test for assessing upper-body push strength. However, its application is constrained by the limitations of current mainstream monitoring technologies, such as linear position transducers (LPTs). These device...
Compared with traditional mine detection methods, UAV-based measures are more suitable for the rapid detection of large areas of scatterable landmines, and a multispectral fusion strategy based on a deep learning model is proposed to facilitate mine...
Landmines remain a significant hazard in contemporary warfare and post-conflict areas, jeopardizing the safety of both civilians and military personnel. This work suggests “Defence Pal,” a cost-effective and portable robotic prototype for...
This paper presents a non-imaging landmine detection system that integrates a highly sensitive multiple-input multiple-output (MIMO) microwave sensor with a machine learning (ML) classifier for automated classification. The proposed sensor consists o...
This reply aims to correct some incomplete/incorrect information provided in the article "A Lightweight and Low-Power UAV-Borne Ground Penetrating Radar Design for Landmine Detection", when the authors compare their results with some state-of-the-art...
Reliable and scalable landmine detection technologies are essential for humanitarian mine action (HMA), yet standardized benchmarks for Unmanned Aerial Vehicle (UAV)-based sensing in operationally relevant environments remain limited. This study pres...
This work proposes a novel Ground Penetrating Radar (GPR) system to detect landmines and Improvised Explosive Devices (IEDs). The system, which was numerically evaluated, is composed of a transmitter placed on a vehicle and looking forward and a rece...
The high-resolution image obtained by ultrawideband synthetic aperture radar (UWB SAR) includes rich features such as shape and scattering features, which can be utilized for landmine discrimination and detection. Due to the high performance and auto...
This paper presents the development of a lightweight and low-power Ground Penetrating Radar (GPR) to detect buried landmines in harsh terrain, using an Unmanned Aerial Vehicle (UAV). Despite the fact that GPR airborne systems have been already used f...
This paper presents methods for the modeling and simulation of explosive target placement in terrain spectral images (i.e., real hyperspectral 90-channel VNIR data), considering unexploded ordnances, landmines, and improvised explosive devices. The m...
Artificial Neural Network (ANN) approaches are applied to detect and determine the object class using a special set of the UltraWideBand (UWB) pulse Ground Penetrating Radar (GPR) sounding results. It used the results of GPR sounding with the antenna...
This work presents an enhanced autonomous airborne Synthetic Aperture Radar (SAR) imaging system able to provide full 3D radar images from the subsurface. The proposed prototype and methodology allow the safe detection of both metallic and non-metall...
The research presented herein provides a first demonstration and a proof of concept of using sensing bacteria (bioreporters) to detect the chemical signatures generated by buried TNT-based landmines in an active minefield. The methodology, based on b...
Background: Velocity-based training (VBT) requires measurement of the velocity at which the barbell is moved in the concentric phase with regard to different resistance exercises, which provides accurate, indirect estimations of 1 RM. However, for as...
We propose a magnetometer system fitted on an unmanned aerial vehicle (UAV, or drone) and a data-processing method for detecting metal antipersonnel landmines (M16) in the demilitarized zone (DMZ) in Korea, which is an undeveloped natural environment...
Buried explosive material, e.g., landmines, represent a severe issue for human safety all over the world. Most explosives consist of environmentally hazardous chemicals like 2,4,6-trinitrotoluene (TNT), carcinogenic 2,4-dinitrotoluene (2,4-DNT) and r...
This study presents an analysis of Landsat data to quantify how the deployment of landmines and demining operations in the first national park in Iraq, the Halgurd-Sakran Core Zone (HSCZ) in the Kurdistan region, has altered the vegetation/land cover...
Among all the forensic applications in which it has become an important exploration tool, ground penetrating radar (GPR) methodology is being increasingly adopted for buried landmine localisation, a framework in which it is expected to improve the op...
Hand-held ground penetrating radar (GPR) systems have been widely applied to landmine detections during recent decades. The accuracy of an imaging result by migration for a hand-held GPR is strongly related to the accuracy of subsurface velocity dist...
A tremendous number of landmines has been buried during the last decade. In recent years, various autonomous platforms equipped with ground-penetrating radars (GPRs) have been proposed for the detection of landmines. These systems have already demons...
An important consideration for UAV-based (unmanned aerial vehicle) object detection in the natural environment is vegetation height and foliar cover, which can visually obscure the items a machine learning model is trained to detect. Hence, the accur...
Use of landmines as a weapon of unconventional warfare rapidly increased in armed conflicts of the last century and some estimates suggest that at least 100 million remain in place across post-conflict nations. Among munitions and explosives of conce...
Existing frameworks for classifying the fidelity for object detection tasks do not consider false positive likelihood and object uniqueness. Inspired by the Detection, Recognition, Identification (DRI) framework proposed by Johnson 1958, we propose a...
In this paper, we obtain the Complex Natural Resonances of an object from the backscattered response in the frequency domain with a novel rational function approximation method based on both Vector Fitting and Cauchy methods. We determine the system...
Ground Penetrating Radar (GPR) has proved to be a successful technique for the detection of landmines and Improvised Explosive Devices (IEDs) buried in the ground. In the last years, novel architectures for safe and fast detection, such as those base...
In recent years, Unmanned Aerial Vehicles (UAV)-based Ground Penetrating Radar (GPR) systems have been developed due to their advantages for safe and fast detection of Improvised Explosive Devices (IEDs) and landmines. The complexity of these systems...
This study proposes a simple deep learning-based framework for image-level anti-personnel landmine detection in long-wave infrared imagery. To address challenges posed by the limited size of the available dataset and the small spatial size of anti-pe...
This paper presents a methodological framework for selectively optimizing computer vision models for safety-critical applications. Through systematic processes of hyperparameter tuning alongside multitask learning, we attempt to create a highly inter...
To design holographic and impulse ground penetrating radar (GPR) sensors suitable for humanitarian de-mining in the Donbass (Ukraine) conflict zone, we measured critical electromagnetic parameters of typical local soils using simple methods that coul...
Landmines and explosive remnants of war are a significant threat in tens of countries and other territories, causing the deaths or injuries of thousands of people every year, even long after military conflicts. Effective technical means of remote det...
Vegetation above the soil surface can have a considerable influence on ground-penetrating radar (GPR) measurements, especially when shallow buried objects are to be detected. Plant water content, biomass, and the structural arrangement of leaves and...
Landmine clearance is an ongoing problem that currently affects millions of people around the world. This study evaluates the effectiveness of ground penetrating radar (GPR) in demining and unexploded ordnance detection using 2.3-GHz and 1-GHz high-...
The genus Bitis comprises 18 species that inhabit Africa and the Arabian Peninsula. They are responsible for a significant proportion of snakebites in the region. The venoms of the two independent lineages of giant Bitis (B. arietans and again in the...
The NATO SPS G-5014 project has shown the possibility of using a holographic RADAR for the detection of anti-personnel mines. To use the RADAR on a robotic scanning system, it must be portable, light, easily integrated with mechanical handling system...
Supervised machine learning algorithms usually require huge labeled data sets to produce sufficiently good results. For many applications, these data sets are still not available today, and the reasons for this can be manifold. As a solution, the mis...
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