Hyperspectral image classification of wolfberry with different geographical origins based on three-dimensional convolutional neural network
The hyperspectral image is a three-dimensional (3D) hypercube with spectral and spatial continuity. Traditional hyperspectral imaging (HSI) processing mainly focuses on spectral information. However, this paper proposed a new hybrid convolutional neural network (New-Hybrid-CNN) algorithm using HSI s...
Guardado en:
Autores principales: | Qingshuang Mu, Zhilong Kang, Yanju Guo, Lei Chen, Shenyi Wang, Yuchen Zhao |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
Taylor & Francis Group
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/a7f8f9e11ffc4fdc8aa0dcc34806a2bc |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
Spectral-Spatial Offset Graph Convolutional Networks for Hyperspectral Image Classification
por: Minghua Zhang, et al.
Publicado: (2021) -
Graph convolutional network method for small sample classification of hyperspectral images
por: ZUO Xibing, et al.
Publicado: (2021) -
A New Convolutional Kernel Classifier for Hyperspectral Image Classification
por: Mohsen Ansari, et al.
Publicado: (2021) -
3D Octave and 2D Vanilla Mixed Convolutional Neural Network for Hyperspectral Image Classification with Limited Samples
por: Yuchao Feng, et al.
Publicado: (2021) -
Deep Spectral Spatial Inverted Residual Network for Hyperspectral Image Classification
por: Tianyu Zhang, et al.
Publicado: (2021)