Object recognition through random scattering media has been an important but challenging task in many fields, such as biomedical imaging, oceanography, security, robotics, and autonomous driving. Numerous computational solutions have been developed to address this problem. However, all of these require large-scale digital computing and consume significant amounts of energy, while still lacking generalization to new random diffusers never used in the training phase.
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Optical computing for object classification through diffusive random media
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