Phys.org  September 20, 2021 Mines are challenging for clearance operations due to their wide area of impact upon deployment, small size, and random minefield orientation. In their previous work a team of researchers in the US (Columbia University, Binghamton University) focused on developing reliable unpiloted aerial systems (UAS) capable of detecting and identifying individual elements of PFM-1 minefields to rapidly assess wide areas for landmine contamination, minefield orientation, and possible minefield overlap. In their most recent proof-of-concept study they designed and deployed a machine learning workflow involving a region-based convolutional neural network (R-CNN) to automate the detection and classification process. […]