Bangladeshi CF Guard: Unveiling Bangladeshi Counterfeit Currency Through Transfer Learning

With recognition of the tremendous risk that counterfeit currency presents to the economic security and stability of Bangladesh, this research employs sophisticated deep neural networks along with transfer learning (TL) techniques to construct a specialized and reliable detection system. A full collection of legitimate and counterfeit Bangladeshi banknotes was assembled, ensuring diversity in denominations and conditions. For the recommended approach, deep neural networks, more particularly convolutional neural networks, were deployed as feature extractors. Models were fine-tuned to discern intricate patterns and variations that separate real from fraudulent currency. A custom CNN model was developed to improve the effectiveness of detection utilizing transfer learning and a dataset with over 6000 samples, which included images of both genuine and counterfeit cashes.