• Rohan Nashte
• Harshada Patil
• Sarthak Deshmukh
• Shruti Aglave
• P. S. Gawali

Counterfeit money notes are expanding step by step, to beat this we proposes an exceptionally accommodating and productive framework to identify the phony cash. For distinguishing the phony cash note is finished by including the quantity of breaks in the string line. For anticipating the note is genuine or counterfeit based on number of interferences. On the off chance that the quantity of interference is zero, assuming it is genuine note in any case it is phony. And furthermore we compute the entropy of the cash notes for the effective discovery of phony money note. Counterfeit money recognition is a major issue around the world, influencing the economy of pretty much every nation including India. Money duplication otherwise called fake cash is a weak danger on economy. It is presently a generally expected peculiarity because of cutting edge printing and checking innovation. The potential arrangements are to utilize either synthetic properties of the money or to utilize its actual appearance. The methodology introduced in this paper depends on actual appearance of the Indian cash. Profound learning calculations have been embraced to remove the which have been taken on as security elements of Indian cash. Consequently, we propose a more easy to use and versatile answer for this issue in type of a work area application.

Currency Detection, Convolutional Neural Network, Neural Network, Deep Learning

"“FAKE CURRENCY DETECTION USING DEEP LEARNING”", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 4, page no.f401-f403, April-2022, Available :http://www.jetir.org/papers/JETIR2204550.pdf

"“FAKE CURRENCY DETECTION USING DEEP LEARNING”", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 4, page no. ppf401-f403, April-2022, Available at : http://www.jetir.org/papers/JETIR2204550.pdf