Satellite Image Segmentation using U-Net.

Author(s)	Mr. Shikhar Singh Yadav, Ms. Rohini Raji, Ms. Mahika Tyagi, Dr. K.P. Jayant
Country	India
Abstract	Satellite image segmentation plays a crucial role in remote sensing tasks like land cover classification, urban planning, and environmental monitoring. Deep learning models, particularly U-Net architectures, have become popular for achieving pixel-wise classification in high-resolution satellite images. By training on labeled datasets and using techniques like data augmentation and hyperparameter tuning, these models can reach high segmentation accuracy, with IoU scores around 0.8. Continued research focuses on improving generalization through methods like attention mechanisms and multi-scale feature fusion.
Keywords	Satellite image segmentation, Remote sensing, Land cover classification, Urban planning, Environmental monitoring, Deep learning, U-Net architecture, Pixel-wise classification, High-resolution satellite images.
Field	Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In	Volume 7, Issue 2, March-April 2025
Published On	2025-04-30
DOI	https://doi.org/10.36948/ijfmr.2025.v07i02.43264
Short DOI	https://doi.org/g9g746

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International Journal For Multidisciplinary Research