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Project in a group of two. It was completed with the help of my classmate Sangram

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Cancer Detection with Siamese Networks and Bagging experimental approach in Pytorch

Challenge: https://iciar2018-challenge.grand-challenge.org/home/

DataSet: https://drive.google.com/file/d/1B8WqyAHgmcNy9VF_2NF7jrwx4ADUCn3L/view?usp=sharing

Our approach to PART A of the challenge posted above.

We have a custom dataset created "SiameseBaggingDataset" which we use and then we have our tests. The ipynb has been formulated for easy understanding and navigation. NOTE: Since our approach takes a comparison with training data during test(considering a siamese comparison) but WE DO NOT USE TEST LABELS except for generating prediction score.

You can find the project requirements in requirements.txt

This project requires python3.6

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Project in a group of two. It was completed with the help of my classmate Sangram

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