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Aerial Image Road Segmentation Task using U-net Variants

The aim of this project is to concieve a classifier capable of discerning the roads from background elements using a small dataset of satellite images originating from Google maps. Both standard convolutional neural networks and U-net variants were implemented and tested. Our best result was achieved using an Attention U-net with extended data augmentation and hyperparameter tuning yielding a F1 score of 0.85 on a hidden test set from AIcrowd.


This repo contains the data, code and environemnt for reproductibility of our results as well as the full report.


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jciardo, frossardr, maverest

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Project carried out with maverest and jciardo as part of the course CS-433

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