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Satellite Image Classification

Satellite image classification is the most significant technique used in remote sensing for the computerized study and pattern recognition of satellite information, which is based on diversity structures of the image that involve rigorous validation of the training samples depending on the used classification algorithm.

Papers

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Showing 26–33 of 33 papers

TitleStatusHype
Recurrent Neural Networks to Correct Satellite Image Classification Maps—0
Enhancing Ship Classification in Optical Satellite Imagery: Integrating Convolutional Block Attention Module with ResNet for Improved Performance—0
Satellite image classification and segmentation using non-additive entropy—0
Satellite image classification methods and Landsat 5TM bands—0
Satellite Image Classification with Deep Learning—0
Satellite image classification with neural quantum kernels—0
SatImNet: Structured and Harmonised Training Data for Enhanced Satellite Imagery Classification—0
2-speed network ensemble for efficient classification of incremental land-use/land-cover satellite image chips—0
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