Oscillatory Neural Networks Implemented on FPGA for Edge Computing Applications - Archive ouverte HAL Accéder directement au contenu
Communication Dans Un Congrès Année : 2023

Oscillatory Neural Networks Implemented on FPGA for Edge Computing Applications

Résumé

This PhD work focuses on Oscillatory Neural Network (ONN) computing paradigm for edge artificial intelligence applications. In particular, it uses a digital ONN design implemented on FPGA to explore novel ONN architectures, learning algorithms, and applications. First, using a fully-connected ONN architecture, ONN can perform pattern recognition, applied in this work for various edge applications, like image processing and robotics. Then, this work introduces layered ONN architectures for classification tasks applied to image edge detection.
Fichier principal
Vignette du fichier
manuscript_v2.pdf (377.5 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-04007911 , version 1 (02-03-2023)

Identifiants

  • HAL Id : hal-04007911 , version 1

Citer

Madeleine Abernot, Aida Todri-Sanial. Oscillatory Neural Networks Implemented on FPGA for Edge Computing Applications. DATE 2023 - 26th Design, Automation and Test in Europe Conference, Apr 2023, Antwerp, Belgium. ⟨hal-04007911⟩
55 Consultations
77 Téléchargements

Partager

Gmail Facebook X LinkedIn More