Document Type
Dissertation
Disciplines
1.2 COMPUTER AND INFORMATION SCIENCE, Computer Sciences
Abstract
Automatic classification and segmentation of land use land cover(LULC) is extremely important for understanding the relationship between humans and nature. Human pressures on the environment have drastically accelerated in the last decades, risking biodiversity and ecosystem services. Remote sensing via satellite imagery is an excellent tool to study LULC. Research has shown that deep learning encoder-decoder architectures have achieved worthy results in the area of LULC, however the application of an ensemble approach has not been well quantified. Studies have shown it to be useful in the area of medical imaging. Ensembling by pooling together predictions to produce better predictions is a well known technique in machine learning. This study aims to quantify the statistical improvement that a deep learning ensemble approach can give to solving a semantic segmentation problem on satellite imagery.
Recommended Citation
Kent, B. (2022). Ensemble Approach to the Semantic Segmentation of Satellite Images. (2022). [Technological University Dublin].
Creative Commons License
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Publication Details
A dissertation submitted in partial fulfilment of the requirements of Technological University Dublin for the degree of M.Sc. in Computing (Data Science) June 16, 2022.