DefaultaideN / EncodeBoosting

Code for the paper: 'A Concatenated Approach Based on Transfer Learning and PCA for Classifying Bees and Wasps'

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EncodeBoosting

Code for the paper: 'A Concatenated Approach Based on Transfer Learning and PCA for Classifying Bees and Wasps' image

Descriptions

This repo contains codes for our paper: 'A Concatenated Approach Based on Transfer Learning and PCA for Classifying Bees and Wasps'. Following is the details for each file.

Encode_boosting

Encode_boosting.ipynb is the training and evaluation process for encode boosting model. You need to get the PCA result before running this code.

Train_model

Train_model.ipynb is the transfer learning part. Including training and evaluation process for the 4 original models.

Evaluate

Evaluate.ipynb is the evaluation process. Metrics used to evaluate the performance were implemented in this file.

Visualize

Visualize.ipynb is the code for the visualizing of heatmaps. You need trained models to perform this progress.

Plot_decompose

Plot_decompose.ipynb is the visualizing and PCA part. Results were used in encode_boosting.ipynb.

Contact

If you have any questions about this project, please feel free to contact us:

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Code for the paper: 'A Concatenated Approach Based on Transfer Learning and PCA for Classifying Bees and Wasps'

License:MIT License


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Language:Jupyter Notebook 100.0%