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• W4387360781 abstract "A compact assembly of photodetectors, enhanced with innovative surface nanostructures, can significantly enhance imaging modalities. This advancement captures multi-dimensional data, including spectral profiles, temporal responses, and spatial resolution. Achieving this breakthrough centers on the meticulous engineering of individual ultrafast detectors, which exhibit diverse responses to identical illumination conditions. A pivotal role is played by the integration of artificial intelligence (AI)-driven computational imaging, which optimizes the obtained multi-dimensional data. This paper demonstrates the benefits of such an imaging method. Specifically, we highlight the potential reductions in the physical scale of current systems, significant enhancements in system sensitivity, and substantial cost reduction. The potential applications include molecular fluorescence signal detection, chem-biological imaging, advanced LiDAR systems, and state-of-the-art focal plane arrays." @default.
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• W4387360781 date "2023-10-05" @default.
• W4387360781 modified "2023-10-06" @default.
• W4387360781 title "Advancing multi-dimensional vision: AI-driven imaging using unique photodetectors with integrated surface nanostructures" @default.
• W4387360781 doi "https://doi.org/10.1117/12.2682104" @default.
• W4387360781 hasPublicationYear "2023" @default.
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