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28 September 2023 Time-lapse image classification using a diffractive optical network
Md Sadman Sakib Rahman, Aydogan Ozcan
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Proceedings Volume PC12655, Emerging Topics in Artificial Intelligence (ETAI) 2023; PC126550R (2023) https://doi.org/10.1117/12.2678185
Event: SPIE Nanoscience + Engineering, 2023, San Diego, California, United States
Abstract
We present a time-lapse approach for image classification that significantly improves the inference of a standalone diffractive optical network. This approach utilizes the information diversity derived from controlled or random lateral displacements of the objects relative to a diffractive optical network, over a finite integration time at the image sensor, to enhance its generalization and statistical inference performance. By employing this time-lapse training and inference, we achieved a numerical blind testing accuracy of 62.03% on grayscale CIFAR-10 images, which represents the highest classification accuracy for this dataset achieved so far using a single diffractive network.
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Md Sadman Sakib Rahman and Aydogan Ozcan "Time-lapse image classification using a diffractive optical network", Proc. SPIE PC12655, Emerging Topics in Artificial Intelligence (ETAI) 2023, PC126550R (28 September 2023); https://doi.org/10.1117/12.2678185
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KEYWORDS
Image classification
Optical networks
Neural networks
Statistical inference
Image enhancement
Image sensors
Information fusion
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