Optimal CNN–Hopfield Network for Pattern Recognition Based on a Genetic Algorithm

Autor: Fekhr Eddine Keddous, Amir Nakib

Publikováno v: Algorithms, Vol 15, Iss 1, p 11 (2021)

Convolutional neural networks (CNNs) have powerful representation learning capabilities by automatically learning and extracting features directly from inputs. In classification applications, CNN models are typically composed of: convolutional layers

Externí odkaz: https://doaj.org/article/ce88ef00bec44f2f823224864aab5775

FPGA acceleration in EVOLVE’s Converged Cloud-HPC Infrastructure

Autor: Fekhr Eddine Keddous, Antony Chazapis, Huy Nam Nguyen, Dimosthenis Masouros, Sotirios Xydis, Angelos Bilas, Jean-Thomas Acquaviva, Konstantina Koliogeorgi, Romain Hugues, Dimitrios Soudris, Michelle Aubrun

Publikováno v: 2021 31st International Conference on Field-Programmable Logic and Applications (FPL)
FPL
31st International Conference on Field-Programmable Logic and Applications (FPL)

The EVOLVE project aims to take important steps in bringing together Big Data, HPC and Cloud domains in a single testbed and expose its services through a user friendly and transparent interface. The EVOLVE testbed is enhanced with acceleration capab

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::29c136da08f2ffd467935e1ca56d26b8