Classification of an object behind a random and unknown scattering medium sets a challenging task for computational imaging and machine vision *** deep learning-based approaches demonstrated the classification of obje...
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Classification of an object behind a random and unknown scattering medium sets a challenging task for computational imaging and machine vision *** deep learning-based approaches demonstrated the classification of objects using diffuser-distorted patterns collected by an image *** methods demand relatively large-scale computing using deep neural networks running on digital ***,we present an all-optical processor to directly classify unknown objects through unknown,random phase diffusers using broadband illumination detected with a single pixel.A set of transmissive diffractive layers,optimized using deep learning,forms a physical network that all-optically maps the spatial information of an input object behind a random diffuser into the power spectrum of the output light detected through a single pixel at the output plane of the diffractive *** numerically demonstrated the accuracy of this framework using broadband radiation to classify unknown handwritten digits through random new diffusers,never used during the training phase,and achieved a blind testing accuracy of 87.74±1.12%.We also experimentally validated our single-pixel broadband diffractive network by classifying handwritten digits"0"and"1"through a random diffuser using terahertz waves and a 3D-printed diffractive *** single-pixel all-optical object classification system through random diffusers is based on passive diffractive layers that process broadband input light and can operate at any part of the electromagnetic spectrum by simply scaling the diffractive features proportional to the wavelength range of *** results have various potential applications in,e.g.,biomedical imaging,security,robotics,and autonomous driving.
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Recently, studies related to human activity recognition have developed which have been applied in various fields. In that field Machine learning and deep learning techniques have been widely used for several classific...
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