Multi Task Learning Based Transformer Model for RealTime Indian Fake Currency Detection & Conversion

Abstract - Economic systems frequently face the problem of counterfeit money circulation, which compromises financial credibility and transaction integrity. Even while manual and UV-based inspection methods are widely utilized, they are time-consuming, prone to human mistake, and inefficient and subjective, hence automated replacements are required. In order to improve and automate the detection of counterfeit cash, this study proposes a hybrid deep learning model that makes use of Transformers, Convolutional Neural Networks (CNNs), and Recurrent Neural Networks (RNNs).