Adoption of Machine Learning in Intelligent Terrain Classification of Hyperspectral Remote Sensing Images

To overcome the difficulty of automating and intelligently classifying the ground features in remote-sensing hyperspectral images, machine learning methods are gradually introduced into the process of remote-sensing imaging. First, the PaviaU, Botswana, and Cuprite hyperspectral datasets are selecte...

Descripción completa

Detalles Bibliográficos
Autores principales: Li, Yanyi, Wang, Jian, Gao, Tong, Sun, Qiwen, Zhang, Liguo, Tang, Mingxiu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2020
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7482030/
https://www.ncbi.nlm.nih.gov/pubmed/32952545
http://dx.doi.org/10.1155/2020/8886932

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7482030/
https://www.ncbi.nlm.nih.gov/pubmed/32952545
http://dx.doi.org/10.1155/2020/8886932

Ejemplares similares