Parmak izi analizinde derin öğrenme

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" Parmak izi analizinde derin öğrenme "
İrtem, Pelin Erdoğmuş, Nesli

Document Type	:	Latin Dissertation
Language of Document	:	English
Record Number	:	1059010
Doc. No	:	TL58127
Main Entry	:	İrtem, Pelin
Title & Author	:	Parmak izi analizinde derin öğrenme\ İrtem, PelinErdoğmuş, Nesli
College	:	Izmir Institute of Technology (Turkey)
Date	:	2020
Degree	:	Master's
student score	:	2020
Note	:	62 p.
Abstract	:	Fingerprints are one of the most widely used personal identification traits. They play a crucial role in forensics because they are considered to be unique to each person. For many years, the identification of individuals had been carried out by human operators. However, with technological developments, automated fingerprint recognition systems have arisen, and the growth in the population has increased the importance of their robustness. On the other hand, deep learning has led to many impressive developments in the area of computer vision. Fingerprint analysis is indeed in the scope of image processing and computer vision; however, the usage of deep learning in fingerprint analysis is rather limited. This study focuses on using deep learning techniques on two different stages of the automated fingerprint recognition pipeline: Fingerprint classification and fingerprint minutiae extraction. Deep learning systems are developed for those two selected stages and analysed with respect to several aspects such as dataset size and different network architectures.
Descriptor	:	Automation
	:	Biometrics
	:	Computer engineering
	:	Deep learning
	:	Fingerprinting
	:	Identification systems
	:	Machine learning
	:	Neural networks
	:	Pattern recognition
Added Entry	:	Erdoğmuş, Nesli
Added Entry	:	Izmir Institute of Technology (Turkey)