Image classification with a 3-Layer SOA-based photonic integrated neural network

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Abstract

We demonstrate for the first time Iris flowers classification by implementing a trained 3-layer neural network with an SOA-based InP cross-connect chip. Classification accuracy of 85.8% is achieved, 9.2% lower than what obtained via a computer.

Original languageEnglish
Title of host publicationOECC/PSC 2019 - 24th OptoElectronics and Communications Conference/International Conference Photonics in Switching and Computing 2019
Place of PublicationPiscataway
PublisherInstitute of Electrical and Electronics Engineers
Number of pages3
ISBN (Electronic)978-4-88552-321-2
DOIs
Publication statusPublished - 1 Jul 2019
Event24th OptoElectronics and Communications Conference/International Conference Photonics in Switching and Computing, OECC/PSC 2019 - Fukuoka, Japan
Duration: 7 Jul 201911 Jul 2019

Conference

Conference24th OptoElectronics and Communications Conference/International Conference Photonics in Switching and Computing, OECC/PSC 2019
CountryJapan
CityFukuoka
Period7/07/1911/07/19

Keywords

  • Neuromorphic computing
  • Photonic integrated circuits

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  • Cite this

    Shi, B., Calabretta, N., & Stabile, R. (2019). Image classification with a 3-Layer SOA-based photonic integrated neural network. In OECC/PSC 2019 - 24th OptoElectronics and Communications Conference/International Conference Photonics in Switching and Computing 2019 [8817694] Piscataway: Institute of Electrical and Electronics Engineers. https://doi.org/10.23919/PS.2019.8817694