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Sensorless camera for digits recognition
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    Machine learning (ML) has been widely applied to image classification. Here, we extend this application to data
    generated by a camera comprised of only a standard CMOS image sensor with no lens. We first created a
    database of lensless images of handwritten digits. Then, we trained a ML algorithm on this dataset. Finally, we demonstrated that the trained ML algorithm is able to classify the digits with accuracy as high as 99% for 2
    digits. Our approach clearly demonstrates the potential for non-human cameras in machine-based decisionmaking scenarios.


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