Zobrazeno 1 - 10
of 39
pro vyhledávání: '"M.H. Shakoor"'
Publikováno v:
Interdisciplinary Neurosurgery, Vol 31, Iss , Pp 101675- (2023)
Objective: Hydrocephalus which is defined as excessive accumulation of cerebrospinal fluid in brain, is one of the most critical entities in pediatric neurosurgery; as it could result in severe developmental delay and neurologic deficits. Imaging eva
Externí odkaz:
https://doaj.org/article/5e72fcf48c1e4ca19f6114183a73469e
Autor:
Reza Boostani, M.H. Shakoor
Publikováno v:
Multimedia Tools and Applications. 80:8639-8666
Applying local binary pattern (LBP) to images with uniform distribution leads to generate discriminative features; however, the distribution of all images is not necessarily uniform. The distribution of an image can be uniformzed if it passes through
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::22a0868eca90ddfab4ab434900e20ef6
https://doi.org/10.1007/s11042-020-10084-4
https://doi.org/10.1007/s11042-020-10084-4
Akademický článek
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Akademický článek
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Autor:
M.H. Shakoor
Publikováno v:
IET Image Processing. 13:877-884
Lung cancer is one of the leading causes of death in the world. Although early detection of lung tumours (nodules) can remarkably diminish the mortal rate, precise detection of them is not always possible by visual inspection of the computerised tomo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8f5e3270dcb4609e3bf9d5aca9319b08
https://doi.org/10.1049/iet-ipr.2018.5070
https://doi.org/10.1049/iet-ipr.2018.5070
An efficient image segmentation scheme for determination of cranial index in scaphocephalic patients
Publikováno v:
Intelligence-Based Medicine. 6:100074
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3ba758ed0d4782d860ff032f739c4812
https://doi.org/10.1016/j.ibmed.2022.100074
https://doi.org/10.1016/j.ibmed.2022.100074
Autor:
Reza Boostani, M.H. Shakoor
Publikováno v:
Multimedia Tools and Applications. 77:21481-21508
Local Binary Pattern (LBP) is one of the best descriptors of texture images; however, it elicits information from the pixels’ value over each locality and therefore its value is highly sensitive to additive noise. In this research, a robust-to-nois
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6583a404828f3e01eb8335650a77bc9c
https://doi.org/10.1007/s11042-017-5440-0
https://doi.org/10.1007/s11042-017-5440-0
Autor:
M.H. Shakoor, Farshad Tajeripour
Publikováno v:
Scientia Iranica. 24:1419-1436
In this paper, it is shown that repeating average lter increases the uniform patterns of noisy textures and, consequently, increases the classi cation accuracy of textures. In other words, for noisy textures, rst, an average lter, such as 3 3 mean fi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7ed0e18e8a7e2f7c079ba4c99f9e688d
https://doi.org/10.24200/sci.2017.4124
https://doi.org/10.24200/sci.2017.4124
Autor:
Reza Boostani, M.H. Shakoor
Publikováno v:
Multimedia Tools and Applications. 77:2561-2591
High computational burden and low accuracy in non-uniform textures are the two main challenges of coral reef classification frameworks. To overcome these drawbacks, two novel forms of mapping approaches are proposed to enable Local Binary Patterns (L
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1bad2465713fb157ac6611c514a160ac
https://doi.org/10.1007/s11042-017-4394-6
https://doi.org/10.1007/s11042-017-4394-6
Autor:
Farshad Tajeripour, M.H. Shakoor
Publikováno v:
Multimedia Tools and Applications. 76:8031-8066
In this paper, a new formula is proposed that uses local entropy for texture feature extraction. This new method is similar to entropy; however, it calculates the local entropy of each local patch of textures. Entropy (ENT) is an attribute that measu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ae37100fa6537d2fd217536d8da7304f
https://doi.org/10.1007/s11042-016-3455-6
https://doi.org/10.1007/s11042-016-3455-6