Deep learning in fingerprint analysis
tarafından
 
İrtem, Pelin, author.

Başlık
Deep learning in fingerprint analysis

Yazar
İrtem, Pelin, author.

Yazar Ek Girişi
İrtem, Pelin, author.

Fiziksel Tanımlama
viii, 53 leaves: charts;+ 1 computer laser optical disc.

Özet
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.

Konu Başlığı
Fingerprints.
 
Neural networks (Computer science).

Yazar Ek Girişi
Erdoğmuş, Nesli,

Tüzel Kişi Ek Girişi
İzmir Institute of Technology. Computer Engineering.

Tek Biçim Eser Adı
Thesis (Master)--İzmir Institute of Technology: Computer Engineering.
 
İzmir Institute of Technology: Computer Engineering--Thesis (Master).

Elektronik Erişim
Access to Electronic Versiyon.


LibraryMateryal TürüDemirbaş NumarasıYer NumarasıDurumu/İade Tarihi
IYTE LibraryTezT002223QA76.87 .I71 2020Tez Koleksiyonu