Self-Supervised Learning of Satellite-Derived Vegetation Indices for Clustering and Visualization of Vegetation Types

Vegetation indices are commonly used techniques for the retrieval of biophysical and chemical attributes of vegetation. This paper presents the potential of an Autoencoders (AEs) and Convolutional Autoencoders (CAEs)-based self-supervised learning approach for the decorrelation and dimensionality re...

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Detalles Bibliográficos
Autores principales: Sharma, Ram C., Hara, Keitarou
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Technical Note
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8321256/
https://www.ncbi.nlm.nih.gov/pubmed/34460629
http://dx.doi.org/10.3390/jimaging7020030

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8321256/
https://www.ncbi.nlm.nih.gov/pubmed/34460629
http://dx.doi.org/10.3390/jimaging7020030

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