Cargando…
Two-Stage Feature Generator for Handwritten Digit Classification
In this paper, a novel feature generator framework is proposed for handwritten digit classification. The proposed framework includes a two-stage cascaded feature generator. The first stage is based on principal component analysis (PCA), which generates projected data on principal components as featu...
Autores principales: | Gunler Pirim, M. Altinay, Tora, Hakan, Oztoprak, Kasim, Butun, İsmail |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10610940/ https://www.ncbi.nlm.nih.gov/pubmed/37896570 http://dx.doi.org/10.3390/s23208477 |
Ejemplares similares
-
Technological Transformation of Telco Operators towards Seamless IoT Edge-Cloud Continuum
por: Oztoprak, Kasim, et al.
Publicado: (2023) -
Application Layer Packet Processing Using PISA Switches
por: Butun, Ismail, et al.
Publicado: (2021) -
Deep Convolutional Extreme Learning Machine and Its Application in Handwritten Digit Classification
por: Pang, Shan, et al.
Publicado: (2016) -
A Novel Handwritten Digit Classification System Based on Convolutional Neural Network Approach
por: Yahya, Ali Abdullah, et al.
Publicado: (2021) -
Convolutional ensembles for Arabic Handwritten Character and Digit Recognition
por: Palatnik de Sousa, Iam
Publicado: (2018)