javad-sheikh / ai4seaice

AI4SeaIce

Table of Contents

1. About This Project
2. Requirements
3. Installation
4. Usage
5. License
6. Contact
7. Acknowledgements

About this project

This project contains the code for a U-Net model architecture used for sea ice charting segmentation. It also contains the names of files used for training and validation (testing). New: Loss functions added for ICLR conference paper. (31/04/2022)

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Requirements

This project uses Python 3.9, and requires PyTorch 1.10.0 library and its dependencies.

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Installation

To install this project either download it as a .zip file and extract it into a desired directory or clone it via the terminal or console command:

• using the HTTPS

git clone https://github.com/astokholm/AI4SeaIce.git

• or SSH

git clone [email protected]:astokholm/AI4SeaIce.git

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Usage

At its current development stage, the scripts in the repository are not meant to be run as executable code, but to provided the details about the architecture and parameters of the models used in sea ice charting experiments (see models). In addition, loss functions have recently been added for an loss comparison paper accepted at the ICLR (see functions).

The training and validation split used in the experiments is available in datalists.

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License

Distributed under MIT licence. See LICENSE for more information.

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Contributors

• Andreas Stokholm
• Andrzej Kucik

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Contact

E-mail: [email protected], [email protected]

Project Link: https://github.com/astokholm/AI4SeaIce

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Acknowledgements

• DTU Space
• ESA Φ-Lab

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