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dengyai/SSP_1000_CNN

Record type:

model
Creator:
den
Host:
CNN-based South Sudan 1,000 SSP banknote authenticity detection system. \# South Sudan 1,000 SSP Banknote Authenticity Detection A Convolutional Neural Network (CNN) project for classifying images of South Sudan 1,000 SSP banknotes as \*\*Genuine\*\* or \*\*Fake\*\*. \## Project Overview This project explores computer vision and deep learning techniques for automated banknote authenticity classification. The system follows a complete machine-learning workflow: 1\. Data collection 2\. Dataset inventory 3\. Image inspection 4\. Image preprocessing 5\. Dataset verification 6\. CNN model development 7\. Model training 8\. Model evaluation 9\. Application development 10\. Deployment \## Classes Class | Description `1000\_Genuine` | Genuine South Sudan 1,000 SSP banknote `1000\_Fake` | Fake/suspected counterfeit South Sudan 1,000 SSP banknote \## Technology Stack \- Python \- TensorFlow \- Keras \- OpenCV \- Pillow \- NumPy \- Pandas \- Streamlit \- Git/GitHub \## Project Structure ```text SSP\_1000\_CNN/ ├── app/# South Sudan 1,000 SSP Banknote Authenticity Detection A Convolutional Neural Network (CNN) project for classifying images of South Sudan 1,000 SSP banknotes as \*\*Genuine\*\* or \*\*Fake\*\*. \## Project Overview This project explores computer vision and deep learning techniques for automated banknote authenticity classification. The system follows a complete machine-learning workflow: 1\. Data collection 2\. Dataset inventory 3\. Image inspection 4\. Image preprocessing 5\. Dataset verification 6\. CNN model development 7\. Model training 8\. Model evaluation 9\. Application development 10\. Deployment \## Classes Class | Description `1000\_Genuine` | Genuine South Sudan 1,000 SSP banknote `1000\_Fake` | Fake/suspected counterfeit South Sudan 1,000 SSP banknote \## Technology Stack \- Python \- TensorFlow \- Keras \- OpenCV \- Pillow \- NumPy \- Pandas \- Streamlit \- Git/GitHub \## Project Structure ```text SSP\_1000\_CNN/ …

Visit

github.com

Tasks

image classificationcomputer vision