On the Application of Data Clustering Algorithm used in Information Retrieval for Satellite Imagery Segmentation

Authors

Ahmed NourEldeen, Department of Mathematics, Faculty of Science, Suez University, Suez, EgyptFollow
Yasser Fouad, Faculty of Computers and Informatics, Suez University, Suez, EgyptFollow
Mohamed E. Wahed, Faculty of Computers and Informatics, Suez Canal University, Ismailia, EgyptFollow
Mohamed S. Metwally, Department of Mathematics, Faculty of Science, Suez University, Suez, EgyptFollow

Abstract

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.

Recommended Citation

NourEldeen, Ahmed; Fouad, Yasser; E. Wahed, Mohamed; and S. Metwally, Mohamed (2023) "On the Application of Data Clustering Algorithm used in Information Retrieval for Satellite Imagery Segmentation," Information Sciences Letters: Vol. 12 : Iss. 6 , PP -.
Available at: https://digitalcommons.aaru.edu.jo/isl/vol12/iss6/43