/unet_satelite_image_segmentation

Using deep learning to tackle the problem of Deep Semantic Segmentation on satellite images

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Satelite Image Segmentation

Segmentation using deep learning is a popular approach to tackle the problem of Deep Semantic Segmentation. The goal is to get a mask composed of 6 categories from a satelite image taken as input, to do so each pixel of the given image must be classified into one of the categories.

Dataset 🛰️

From Dubai's Mohammed Bin Rashid Space Center.

The dataset consists of aerial imagery of Dubai obtained by MBRSC satellites and annotated with pixel-wise semantic segmentation in 6 classes.

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Image Mask