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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. In the first formulation it is assumed that sufficient training data are available, and a POMDP model is designed based on physics-based features, with model selection performed via a variational Bayes analysis of several possibledoi:10.1109/tgrs.2007.894933 fatcat:4qlujos4pvb3jlljtnmvf3nw4y