Butterfly landmines mapped by drones and machine learning

The team had previously developed a method that allowed for the accurate detection of butterfly landmines using low-cost commercial drones equipped with infrared cameras.

EPSRC-funded project takes dual approach to clearing landmines

Their new research focuses on automated detection of landmines using convolutional neural networks (CNN), which they say is the standard machine learning method for object detection and classification in the field of remote sensing. This method is a game-changer in the field, said Alek Nikulin, assistant professor of energy geophysics at Binghamton University.

"All our previous efforts relied on human-eye scanning of the dataset," Nikulin said in a statement. "Rapid drone-assisted mapping and automated detection of scatterable mine fields would assist in addressing the deadly legacy of widespread use of small scatterable landmines in recent armed conflicts and allow to develop a functional framework to effectively address their possible future use."