Butterfly Species Classification Model using Deep Learning

[IkkiOcean]

Pull Request: Butterfly Species Classification Model using Deep Learning

Description

a deep learning model for the classification of butterfly species. The model employs various neural network architectures, demonstrating impressive accuracy in identifying different butterfly species.

Models Used and Accuracy

The following models were utilized in this project, along with their respective accuracy rates:

Model	Accuracy
Convolutional Neural Network (CNN)	87.36%
ResNet50	80.82%
EfficientNet	91.85%

Summary of Results

• EfficientNet achieved the highest accuracy at 91.85%, showcasing its effectiveness for species classification tasks.
• CNN performed well with an accuracy of 87.36%, indicating its viability for this application.
• ResNet50 had an accuracy of 80.82%, serving as a solid benchmark.

Purpose

The purpose of this model is to assist researchers in efficiently identifying butterfly species, which is critical for biodiversity research and conservation efforts. By leveraging deep learning techniques, we aim to enhance data collection and analysis in ecological studies.

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• Closes 💡[Feature]: Add Butterfly Species Classification Model using DL #1343

Type of change

• Added a new DL model and its evaluation
• Added proper Documentation for it

Checklist:

• My code follows the style guidelines of this project
• I have performed a self-review of my own code
• I have commented my code, particularly in hard-to-understand areas
• I have made corresponding changes to the documentation
• My changes generate no new warnings

[github-actions]

Thank you for submitting your pull request! 🙌 We'll review it as soon as possible. In the meantime, please ensure that your changes align with our CONTRIBUTING.md. If there are any specific instructions or feedback regarding your PR, we'll provide them here. Thanks again for your contribution! 😊

[IkkiOcean]

please add level 3 since I have created 3 different notebooks with different models and evaluated them
@sanjay-kv