This repository contains the code for an image classification project that utilizes deep learning techniques for accurate classification.
The project was developed using PyTorch, a widely adopted deep learning framework known for its flexibility and ease of use.
The models were trained on a comprehensive dataset consisting of 100,000 images, and their performance was evaluated on an independent test set comprising 10,000 images.
| Model | Dataset | Accuracy |
|---|---|---|
| AlexNet | Natural Images | 98% |
| VGG | Natural Images | 98% |
| Your CNN | Natural Images | 88% |
| EfficientNet-B1 | Birds Species | 95% |
| EfficientNet-B4 | Birds Species | 85% |
| AlexNet | Birds Species | 94% |
To explore this project:
- Clone the repository:
git clone https://github.com/leilibrk/Image-Classification-Deep-Learning.git - Set up your environment and dependencies. Consider using virtual environments or containers.
- Access the Jupyter Notebook files to review the code and results interactively.
We extend our appreciation to the PyTorch community for providing an excellent platform for deep learning research and development.
Contributions to this repository are welcome! Feel free to fork and create pull requests for any improvements or enhancements.