id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
work_zmzfnu5br5grbipquovhai5d7a	Toqeer Ali	DeepMoney: counterfeit money detection using generative adversarial networks	2019	21	.pdf	application/pdf	6537	797	55	learning called Generative Adversarial Networks (GANs) are employed. Keywords Deep Learning, Counterfeit Money, Generative Adversarial Networks DeepMoney: counterfeit money detection using generative adversarial networks. genuine ones, state-of-the-art models of machine learning called Generative Adversarial used class descriptions for real and fake images of the currency for security threads in the fingerprint records which can be used for detecting counterfeit currency note. To differentiate between genuine and counterfeit notes, the researchers used a threedimensional imaging security feature according to the FF-OCT system. Kang & Lee (2016) Fake banknote detection Multispectral imaging sensors Feature extraction and classification require high computation Mirza & Nanda (2012a) Currency verification Image processing: edge detection generative and discriminative models for the recognition of real and counterfeit currency generative model G was used to input the counterfeit notes to classify with discriminative Generative Adversarial Networks cope with real and fake data. Image processing based detection of counterfeit	./cache/work_zmzfnu5br5grbipquovhai5d7a.pdf	./txt/work_zmzfnu5br5grbipquovhai5d7a.txt