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001-es BibID:	BIBFORM063707
Első szerző:	Azodinia, Mohammadreza (informatikus)
Cím:	A method for image retrieval using combination of color and frequency layers / Mohammad Reza Azodinia, András Hajdu
Dátum:	2015
ISSN:	0975-8887
Megjegyzések:	In this paper a fast and effective noise-resistant method for image retrieval has been proposed. In this method, first, the image is decomposed into different frequency layers using complex wavelet transform so as to make it possible to extract the texture features of the image. Thereafter, in the HSV color space, each layer is quantized into 166 different colors and the color histogram is calculated for each layer. Furthermore, a number of statistical features are extracted from each sub-image using complex wavelet transform, which are used along with other features for image retrieval. In order to verify the effectiveness of the proposed method, it has been evaluated using a dataset containing 3000 images and compared to a competent method in this field. The results prove the superiority of the proposed method.
Tárgyszavak:	Műszaki tudományok Informatikai tudományok idegen nyelvű folyóiratközlemény külföldi lapban Color feature complex wavelet transform Content-based image retrieval feature extraction histogram image processing texture feature
Megjelenés:	International Journal of Computer Applications 118 : 3 (2015), p. 10-13. -
További szerzők:	Hajdu András (1973-) (matematikus, informatikus)
Pályázati támogatás:	NK101680 OTKA TAMOP-4.2.2.C-11/1/KONV2012-0001 TÁMOP TAMOP-4.2.2.A-11/1/KONV-2012-0045 TÁMOP TÁMOP 4.2.4. A/2-11-1-2012-0001 TÁMOP
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001-es BibID:	BIBFORM086227
Első szerző:	Moghadasi, Mohammad (informatikus)
Cím:	Cloud Computing Auditing : roadmap and process / Mohammad Moghadasi, Seyed Majid Mousavi, Gábor Fazekas
Dátum:	2018
ISSN:	2158-107X 2156-5570
Megjegyzések:	Cloud Computing is a new form of IT system and infrastructure outsourcing as an alternative to traditional IT Outsourcing (ITO). Hence, migration to cloud computing is rapidly growing among organizations. Adopting this technology brings numerous positive aspects, although imposing different risks and concerns to organization. An organization which officially deputes its cloud computing services to outside (offshore or inshore) providers and implies that it outsources its functions and process of its IT to external BPO services providers. Therefore, customers of cloud must evaluate and manage the IT infrastructure construction and the organization's IT control environment of BPO vendors [25]. Since cloud is an internet-based technology, cloud auditing would be very critical and challengeable in such an environment. This paper focuses on practices related to auditing processes, methods, techniques, standards and frameworks in cloud computing environments.
Tárgyszavak:	Műszaki tudományok Informatikai tudományok idegen nyelvű folyóiratközlemény külföldi lapban folyóiratcikk
Megjelenés:	International Journal of Advanced Computer Science and Applications. - 9 : 12 (2018), p. 467-472. -
További szerzők:	Mousavi, Seyedmajid (1982-) (informatika) Fazekas Gábor (1952-) (informatikus, matematikus)
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001-es BibID:	BIBFORM086226
035-os BibID:	(WoS)000485682500027 (Scopus)85070095162
Első szerző:	Moghadasi, Mohammad (informatikus)
Cím:	An Automatic Multiple Sclerosis Lesion Segmentation Approach based on Cellular Learning Automata / Moghadasi, Mohammad; Fazekas, Gabor
Dátum:	2019
ISSN:	2158-107X 2156-5570
Megjegyzések:	Multiple Sclerosis (MS) is a demyelinating nerve disease which for an unknown reason assumes that the immune system of the body is affected, and the immune cells begin to destroy the myelin sheath of nerve cells. In Pathology, the areas of the distributed demyelination are called lesions that are pathologic characteristics of the Multiple Sclerosis (MS) disease. In this research, the segmentation of the lesions from one another is studied by using gray scale features and the dimensions of the lesions. The brain Magnetic Resonance Imaging (MRI) images in three planes (T1, T2, PD)1,2,3 containing MS disease lesions have been used. Cellular Learning Automata (CLA) is applied on the MRI images with a novel trial and error approach to set penalty and reward frames for each pixel. The images were analyzed in MATLAB and the results show the MS disease lesions in white and the brain anatomy in red on a black background. The proposed approach can be considered as a supplementary or superior method for other methods such as Graph Cuts (GC), fuzzy c-means, mean-shift, k-Nearest Neighbor (KNN), Support Vector Machines (SVM).
Tárgyszavak:	Műszaki tudományok Informatikai tudományok idegen nyelvű folyóiratközlemény külföldi lapban folyóiratcikk
Megjelenés:	International Journal of Advanced Computer Science and Applications. - 10 : 7 (2019), p. 178-183. -
További szerzők:	Fazekas Gábor (1952-) (informatikus, matematikus)
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