A generic intelligent tomato classification system for practical applications using DenseNet-201 with transfer learning
Abstract A generic intelligent tomato classification system based on DenseNet-201 with transfer learning was proposed and the augmented training sets obtained by data augmentation methods were employed to train the model. The trained model achieved high classification accuracy on the images of diffe...
Guardado en:
Autores principales: | Tao Lu, Baokun Han, Lipin Chen, Fanqianhui Yu, Changhu Xue |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
Nature Portfolio
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/9dd87356d6194258bcebc8b227504420 |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
Author Correction: A generic intelligent tomato classification system for practical applications using DenseNet-201 with transfer learning
por: Tao Lu, et al.
Publicado: (2021) -
Intelligent Fault Diagnosis and Forecast of Time-Varying Bearing Based on Deep Learning VMD-DenseNet
por: Shih-Lin Lin
Publicado: (2021) -
Landslide Detection Mapping Employing CNN, ResNet, and DenseNet in the Three Gorges Reservoir, China
por: Tong Liu, et al.
Publicado: (2021) -
Corrections to “Robust Motor Imagery Classification Using Sparse Representations and Grouping Structures”
por: Vangelis P. Oikonomou, et al.
Publicado: (2021) -
Light-Convolution Dense Selection U-Net (LDS U-Net) for Ultrasound Lateral Bony Feature Segmentation
por: Sunetra Banerjee, et al.
Publicado: (2021)