Semantic segmentation model for land cover classification from satellite images in Gambella National Park, Ethiopia

Abstract

Article highlights Built semantic segmentation models using machine learning classifiers (SVM and RF), and deep learning using LinkNet with ResNet34 as encoder techniques. Presents the semantic segmentation for land cover classification. Compare and contrast the machine learning classifiers and deep learning techniques performance.

Keywords

• Satellite images
• Land cover classification
• Semantic segmentation
• Gambella National Park