FocusNET: An autofocusing learning‐based model for digital lensless holographic microscopy
ABSTRACT: This paper reports on a convolutional neural network (CNN) – based regression model, called FocusNET, to predict the accurate reconstruction distance of raw holograms in Digital Lensless Holographic Microscopy (DLHM). This proposal provides a physical-mathematical formulation to extend its...
- Autores:
-
Pabón Vidal, Adriana Lucía
García Sucerquia, Jorge Iván
Gómez Ramírez, Alejandra
Herrera Ramírez, Jorge Alexis
Buitrago Duque, Carlos Andrés
Lopera Acosta, María Josef
Montoya, Manuel
Trujillo Anaya, Carlos Alejandro
- Tipo de recurso:
- Article of investigation
- Fecha de publicación:
- 2023
- Institución:
- Universidad de Antioquia
- Repositorio:
- Repositorio UdeA
- Idioma:
- eng
- OAI Identifier:
- oai:bibliotecadigital.udea.edu.co:10495/42049
- Acceso en línea:
- https://hdl.handle.net/10495/42049
- Palabra clave:
- Aprendizaje Profundo
Deep Learning
Microscopía
Microscopy
https://id.nlm.nih.gov/mesh/D000077321
https://id.nlm.nih.gov/mesh/D008853
- Rights
- openAccess
- License
- http://creativecommons.org/licenses/by-nc-nd/2.5/co/