Human-in-the-Loop Hyperspectral Imaging Optimizes UAV Landmine Detection
RITiger · hf · 2026-07-30
This paper investigates the use of UAV visible and near-infrared (VNIR) hyperspectral imaging (HSI) for the detection of PFM-1 landmines.
To reduce the false alarm rate during operational screening, the researchers compared various algorithms (such as SAM, MF, ACE, and CEM) and different signature extraction strategies. They introduced a simulated human-in-the-loop signature bootstrap mechanism.
Experiments revealed that while fully informed methods reach ideal performance after verifying all seven target regions, the required inspection effort varies dramatically across algorithms. The ACE algorithm confirms all regions in just two rounds and nine candidate inspections, whereas SAM variants require thousands of candidate reviews to locate their final targets.
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