Abstract

A model of a multispectral camera that can capture images at five wavelengths—532, 612, 780, 850, and 940 nm—is designed and fabricated. The obtained multispectral images are analyzed. Algorithms of artificial neural network operation in the processing of multispectral images are discussed. A convolutional neural network for identification and classification of multispectral images in real-time is developed.

© 2021 Optical Society of America

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