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Using Microwave Metamaterials in Machine Learning Speeds Object Recognition

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A new approach to object identification, developed by researchers at Duke University and the Institut de Physique de Nice (INPHYNI), enables joint learning of optimal measurement strategies and a matching processing algorithm, and uses inferred knowledge about task, scene, and measurement constraints to improve the accuracy of object recognition tasks while using a limited number of measurements. The approach uses microwave patterns to increase accuracy and reduce computing time and power requirements. The researchers used a metamaterial antenna that can sculpt a microwave wavefront...Read full article

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