Skip to content
Descubridor Institucional UMAR
Inicio
Búsqueda avanzada
Explorar
Inicio
Búsqueda avanzada
Explorar
Login
Language
English
Deutsch
Español
Français
Italiano
All Fields
Title
Author
Subject
Call Number
ISBN/ISSN
Tag
Find
Advanced
End-to-end deep learning of geometric shaping for unamplified coherent systems
End-to-end deep learning of geometric shaping for unamplified coherent systems
Fuente:
Zenodo
Saved in:
Bibliographic Details
Main Authors:
Oliveira, B. M.
,
Neves, M. S.
,
Guiomar, F. P.
,
Medeiros, M. C. R.
,
Monteiro, Paulo P.
Format:
Recurso digital
Published:
Zenodo
2025
Online Access:
Acceder al recurso
Tags:
Add Tag
No Tags, Be the first to tag this record!
Cite this
Text this
Email this
Print
Export Record
Export to RefWorks
Export to EndNoteWeb
Export to EndNote
Save to List
Permanent link
Holdings
Description
Comments
Similar Items
Staff View
Internet
https://doi.org/10.1364/OE.468836
Similar Items
Capacity-achieving probabilistic constellation shaping for unamplified coherent links
by: Oliveira, B. M., et al.
Published: (2023)
End-to-end deep learning for superoscillatory subtraction imaging
by: Jin, Zhongwei, et al.
Published: (2025)
End‐to‐end light‐weighted deep‐learning model for abnormality classification in kidney CT images
by: V. Karthikeyan, et al.
Published: (2024)
End-to-end plaque counting and virus titration from laboratory plate images with deep learning
by: Moris, Eugenia, et al.
Published: (2026)
End-to-end differentiable design of geometric waveguide displays
by: Yang, Xinge, et al.
Published: (2026)