Jun 16, 2021 · Two learning approaches are proposed and compared for classifying a large-scale dataset including different types of land-use and land-cover surfaces.
Traditional (shallow) machine learning models and deep learning models are built by using a set of features extracted from the satellite images for both ...
Traditional (shallow) machine learning models and deep learning models are built by using a set of features extracted from the satellite images for both ...
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Dec 9, 2022 · The shallow approach had the best F1-score of 0.87, while the deep approach ResNet50 achieved the best F1-score of 0.924. It has been realized ...
Dec 11, 2022 · The shallow approach had the best F1-score of 0.87, while the deep approach ResNet50 achieved the best F1-score of 0.924. It has been realized ...
This repository provides an exhaustive overview of deep learning techniques specifically tailored for satellite and aerial image processing.
Sep 21, 2023 · This article targets shallow models due to their interpretable nature to assess the presence of LiDAR data for supervised segmentation.
State-of-the-art machine learning algorithms have shown to perform well in satellite image classification, often resulting in overall accuracies that exceed the ...
Jul 13, 2021 · Bibliographic details on Satellite Imagery Classification Using Shallow and Deep Learning Approaches.
In brief, this Research Topic approaches themes in deep learning for remotely sensed image classification both from the operational and applications ...