Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Cuenat Stéphane"'
Autor:
Cuenat Stéphane, Brito Carcaño Jesús E., Ahmad Belal, Sandoz Patrick, Couturier Raphaël, Laurent Guillaume J., Jacquot Maxime
Publikováno v:
Journal of the European Optical Society-Rapid Publications, Vol 20, Iss 2, p 31 (2024)
Deep neural networks (DNNs) are increasingly employed across diverse fields of applied science, particularly in areas like computer vision and image processing, where they enhance the performance of instruments. Various advanced coherent imaging tech
Externí odkaz:
https://doaj.org/article/38f02a81e44b44ac9513d0764c8a98b3
Autor:
Brito Carcaño Jesús E., Cuenat Stéphane, Ahmad Belal, Sandoz Patrick, Couturier Raphaël, Laurent Guillaume, Jacquot Maxime
Publikováno v:
EPJ Web of Conferences, Vol 287, p 13011 (2023)
Deep neural networks are increasingly applied in many branches of applied science such as computer vision and image processing by increasing performances of instruments. Different deep architectures such as convolutional neural networks or Vision Tra
Externí odkaz:
https://doaj.org/article/0f92c26cd6294194b928b7ee9e9a07c2
Autor:
Cuenat, Stéphane, Andréoli, Louis, André, Antoine N., Sandoz, Patrick, Laurent, Guillaume J., Couturier, Raphaël, Jacquot, Maxime
The numerical wavefront backpropagation principle of digital holography confers unique extended focus capabilities, without mechanical displacements along z-axis. However, the determination of the correct focusing distance is a non-trivial and time c
Externí odkaz:
http://arxiv.org/abs/2203.07772
Autor:
Cuenat, Stéphane, Couturier, Raphaël
In Digital Holography (DH), it is crucial to extract the object distance from a hologram in order to reconstruct its amplitude and phase. This step is called auto-focusing and it is conventionally solved by first reconstructing a stack of images and
Externí odkaz:
http://arxiv.org/abs/2108.09147