Comparing CNN- and Transformer-Based Deep Learning Models for Semantic Segmentation of Remote Sensing Images. Specifically looking at different configurations of U-Net and SegFormer applied to Potsdam, Vaihingen and FloodNet dataset.
Developed deep learning based architecture model which perform semantic segmentation for post-flood images using VGG16 pre-trained model and Unet architecture.
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