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Toplam kayıt 7, listelenen: 1-7
Performance analysis of GLCM-based classification on Wavelet Transform-compressed fingerprint images
(IEEE, 2016)
Fingerprint detection is one of the primary methods for identifying individuals. Gray Level Co-occurrence Matrix (GLCM) is the oldest and prominent statistical textual feature extraction method applied in many fields for ...
A novel high-performance holistic descriptor for face retrieval
(Springer London, 2020)
Texture extraction-based classification has become the facto methodology applied in face recognition. Haralick feature extraction from gray-level co-occurrence matrix (GLCM) is one of the basic holistic studies that has ...
DLGBD: A directional local gradient based descriptor for face recognition
(Springer, 2019)
This paper proposes a novel high-performance gradient-based local descriptor that handles the prominent challenges of face recognition such as resistance against rotational, illuminative changes as well as noise effects. ...
A machine learning-based framework for predicting game server load
(Springer, 2020)
Server load prediction can be utilized for load-balancing and load-sharing in distributed systems. The use of machine learning (ML) algorithms for load estimation in distributed system applications can increase the ...
FTSH: a framework for transition from square image processing to hexagonal image processing
(Springer, 2020)
This paper proposes a novel framework for transition from the ordinary square-pixel-based image processing (SIP) domain to the hexagonal-pixel-based (HIP) domain (FTSH). The conventional image acquisition and processing ...
Effect of derivative action on back-propagation algorithms
(Springer Verlag, 2019)
Multilayer neural networks using supervised training try to minimize the error between a given correct answer and the ones produced by the network. The weights in the neural network are adjusted at each iteration and after ...
RIMFRA: Rotation-invariant multi-spectral facial recognition approach by using orthogonal polynomials
(Springer New York LLC, 2019)
This paper proposes a novel rotation-invariant multi-spectral facial recognition approach (RIMFRA) by using orthogonal polynomials. In the first step, a rotation, illumination and noise invariant local descriptor (RinLd) ...