DEEP LEARNING BASED COUNTERFEIT CURRENCY DETECTION SYSTEM
Aditya Yellapantula, Yasaswini Natte, Pallavi Salapati, Chaitanya Pagolu, Venkata Narayana Poleboina · Fuzzy Systems and Soft Computing · 2025
The headway of variety printing innovation has expanded the commonness of fake money creation for an enormous scope. In spite of the rising pervasiveness of electronic financial exchanges and the declining utilization of "paper currency", banknotes keep on being disseminated because of their "dependability and convenience". Quite a while prior, printing was selective to printing houses; at the same time, today, anybody might deliver currency paper with striking accuracy utilizing a standard laser printer. Thusly, the pervasiveness of fake money has heightened in contrast with authentic currency. India has denounced issues like debasement, dark cash, and the falsifying of money notes, which are critical worries. A deep learning-based strategy is introduced to distinguish fake Indian money. The "MATLAB" apparatus has been utilized to distinguish fake currency. The outcome will decide whether the Indian rupee note is bona fide or counterfeit. Preface A clever age of shopping baskets using profound learning has arisen, working with a more helpful encounter for buyers. Attire proposal algorithms frequently recommend corresponding outfits or other style things for clients to think about getting [1]. Not at all like the far reaching outfit idea framework that suggests pieces of clothing with amicable examples and varieties, "stylish match recommendation(SMR)" framework offers stylish things that upgrade the outfits a client has previously picked, for example, planning "jeans and shirts" [7]-[11]. The SMR framework is broke down.