Cargando…
Automated human cell classification in sparse datasets using few-shot learning
Classifying and analyzing human cells is a lengthy procedure, often involving a trained professional. In an attempt to expedite this process, an active area of research involves automating cell classification through use of deep learning-based techniques. In practice, a large amount of data is requi...
Autores principales: | Walsh, Reece, Abdelpakey, Mohamed H., Shehata, Mohamed S., Mohamed, Mostafa M. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8861170/ https://www.ncbi.nlm.nih.gov/pubmed/35190567 http://dx.doi.org/10.1038/s41598-022-06718-2 |
Ejemplares similares
-
CORONA-Net: Diagnosing COVID-19 from X-ray Images Using Re-Initialization and Classification Networks
por: Elbishlawi, Sherif, et al.
Publicado: (2021) -
Insights into few shot learning approaches for image scene classification
por: Soudy, Mohamed, et al.
Publicado: (2021) -
Automated classification of polyps using deep learning architectures and few-shot learning
por: Krenzer, Adrian, et al.
Publicado: (2023) -
N-Omniglot, a large-scale neuromorphic dataset for spatio-temporal sparse few-shot learning
por: Li, Yang, et al.
Publicado: (2022) -
Study of the Few-Shot Learning for ECG Classification Based on the PTB-XL Dataset
por: Pałczyński, Krzysztof, et al.
Publicado: (2022)