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On the Application of Data Clustering Algorithm used in Information Retrieval for Satellite Imagery Segmentation |
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PP: 2739-2746 |
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doi:10.18576/isl/120643
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Author(s) |
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Ahmed NourEldeen,
Yasser Fouad,
Mohamed E. Wahed,
Mohamed S. Metwally,
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Abstract |
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| This study proposes an automated technique for segmenting satellite imagery using unsupervised learning. Autoencoders, a type of neural network, are employed for dimensionality reduction and feature extraction. The study evaluates different segmentation architectures and encoders and identifies the best performing combination as the DeepLabv3+ architecture with a ResNet-152 encoder. This approach achieves high performance scores across multiple metrics and can be beneficial in various fields, including agriculture, land use monitoring, and disaster response.
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