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  • 2019 Conference on Lasers and Electro-Optics Europe and European Quantum Electronics Conference
  • OSA Technical Digest (Optica Publishing Group, 2019),
  • paper ci_2_1

Wavelength Independent Image Classification Through A Multimode Fiber Using Deep Neural Networks

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Deep Neural Networks (DNNs) have been increasingly implemented in different research fields or industrial applications. Large amounts of data are processed daily in order to extract useful information using machine learning techniques. Many research groups have shown impressive results on improving resolution in microscopy and quantitative phase retrieval by training DNNs on real datasets [1,2]. Recently, recovery and reconstruction of images after they have propagated through multimode optical fibers (MMFs) have also been achieved using DNNs [3,4]. When images propagate through MMFs they suffer severe scrambling because the information gets distributed among the different spatial modes that the fiber supports.

© 2019 IEEE

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