Convolutional neural network transformer (CNNT) for fluorescence microscopy image denoising with improved generalization and fast adaptation
- Standort
-
Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
-
1 Online-Ressource.
- Sprache
-
Englisch
- Erschienen in
-
Convolutional neural network transformer (CNNT) for fluorescence microscopy image denoising with improved generalization and fast adaptation ; volume:14 ; number:1 ; day:6 ; month:8 ; year:2024 ; pages:1-12 ; date:12.2024
Scientific reports ; 14, Heft 1 (6.8.2024), 1-12, 12.2024
- Urheber
-
Rehman, Azaan
Zhovmer, Alexander
Sato, Ryo
Mukouyama, Yoh-suke
Chen, Jiji
Rissone, Alberto
Puertollano, Rosa
Liu, Jiamin
Vishwasrao, Harshad D.
Shroff, Hari
Combs, Christian A.
Xue, Hui
- Beteiligte Personen und Organisationen
-
SpringerLink (Online service)
- DOI
-
10.1038/s41598-024-68918-2
- URN
-
urn:nbn:de:101:1-2410262105081.633223622307
- Rechteinformation
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
15.08.2025, 07:24 MESZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Beteiligte
- Rehman, Azaan
- Zhovmer, Alexander
- Sato, Ryo
- Mukouyama, Yoh-suke
- Chen, Jiji
- Rissone, Alberto
- Puertollano, Rosa
- Liu, Jiamin
- Vishwasrao, Harshad D.
- Shroff, Hari
- Combs, Christian A.
- Xue, Hui
- SpringerLink (Online service)
Ähnliche Objekte (12)
Spatial redundancy transformer for self-supervised fluorescence image denoising
Transformer-based convolutional forgetting knowledge tracking
A denoising-classification neural network for power transformer protection
Hformer: highly efficient vision transformer for low-dose CT denoising
LGIT: local–global interaction transformer for low-light image denoising
Ovarian tumor diagnosis using deep convolutional neural networks and a denoising convolutional autoencoder
Conditioned fully convolutional denoising autoencoder for multi-target NILM
Transformer and Graph Convolutional Network for Text Classification
Methods for image denoising using convolutional neural network: a review
Author Correction: Ovarian tumor diagnosis using deep convolutional neural networks and a denoising convolutional autoencoder
Learning cartographic building generalization with deep convolutional neural networks
Gct-TTE: graph convolutional transformer for travel time estimation
Spatial redundancy transformer for self-supervised fluorescence image denoising
Transformer-based convolutional forgetting knowledge tracking
A denoising-classification neural network for power transformer protection
Hformer: highly efficient vision transformer for low-dose CT denoising
LGIT: local–global interaction transformer for low-light image denoising
Ovarian tumor diagnosis using deep convolutional neural networks and a denoising convolutional autoencoder
Conditioned fully convolutional denoising autoencoder for multi-target NILM
Transformer and Graph Convolutional Network for Text Classification
Methods for image denoising using convolutional neural network: a review
Author Correction: Ovarian tumor diagnosis using deep convolutional neural networks and a denoising convolutional autoencoder
Learning cartographic building generalization with deep convolutional neural networks
Gct-TTE: graph convolutional transformer for travel time estimation
Spatial redundancy transformer for self-supervised fluorescence image denoising
Transformer-based convolutional forgetting knowledge tracking
A denoising-classification neural network for power transformer protection
Hformer: highly efficient vision transformer for low-dose CT denoising
LGIT: local–global interaction transformer for low-light image denoising
Ovarian tumor diagnosis using deep convolutional neural networks and a denoising convolutional autoencoder
Conditioned fully convolutional denoising autoencoder for multi-target NILM
Transformer and Graph Convolutional Network for Text Classification
Methods for image denoising using convolutional neural network: a review
Author Correction: Ovarian tumor diagnosis using deep convolutional neural networks and a denoising convolutional autoencoder
Learning cartographic building generalization with deep convolutional neural networks