This project focuses on developing an AI-based system for detecting and classifying coins in images. By leveraging computer vision techniques and machine learning algorithms, the system aims to accurately identify various coin denominations from photographic inputs.
Data Acquisition: Collected a comprehensive dataset of coin images, capturing various denominations under diverse lighting and orientation conditions.
Preprocessing: Enhanced image quality and model robustness through resizing, normalization, and augmentation techniques.
Model Architecture: Developed convolutional neural networks (CNNs) to extract features and classify coins based on visual characteristics.
Training and Validation: Trained the model on labeled datasets and evaluated performance using metrics like accuracy and confusion matrices.