We give an outline of camera-based computer vision technology in this paper. It can aid those who are not visually
blessed in instantly identifying paper currency. For those who are blind or visually challenged, an effective paper money
detection algorithm should have the following qualities: 1) Complete precision; and 2) adaptability in a range of circumstances
in various environments and emergence. Many of the currency identification algorithms in use today are constrained to specific
situations. We suggest a deep learning strategy focused on high accuracy in this project. This method works well for gathering
more class-specific data and is better at handling partial closure and viewpoint changes. Evaluation of transfer learning also
demonstrate its efficiency in coping with visual rotation, measures, and illumination changes.
