Efficient Deep Semantic Segmentation for Land Cover Classification Using Sentinel Imagery

Efficient Deep Semantic Segmentation for Land Cover Classification Using Sentinel Imagery

Nowadays, different machine learning approaches, either conventional or more advanced, use input from different remote sensing imagery for land cover classification and associated decision making. However, most approaches rely heavily on time-consuming tasks to gather accurate annotation data. Furth...

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Bibliographic Details
Main Authors: Anastasios Tzepkenlis, Konstantinos Marthoglou, Nikos Grammalidis
Format: Article
Language:English
Published: MDPI AG 2023-04-01
Series:Remote Sensing
Subjects:
convolutional neural networks
deep neural networks
land cover classification
machine learning
random forest
Sentinel-1
Online Access:https://www.mdpi.com/2072-4292/15/8/2027

Internet

https://www.mdpi.com/2072-4292/15/8/2027

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