Zobrazeno 1 - 10
of 160
pro vyhledávání: '"Mounir SAYADI"'
Publikováno v:
Frontiers in Signal Processing, Vol 4 (2024)
IntroductionKnee osteoarthritis (KOA) is a major health issue affecting millions worldwide. This study employs machine learning algorithms to analyze human gait using kinematic data, aiming to enhance the diagnosis and detection of KOA. By adopting t
Externí odkaz:
https://doaj.org/article/1c5b25ab3c0449f2af114b894cfd342d
Publikováno v:
Frontiers in Computational Neuroscience, Vol 18 (2024)
IntroductionAlzheimer’s disease (AD) is a progressive neurodegenerative disorder characterized by cognitive decline, memory loss, and impaired daily functioning. Despite significant research, AD remains incurable, highlighting the critical need for
Externí odkaz:
https://doaj.org/article/0bbba1ba3cf24279923aa4ca75b47764
Publikováno v:
Frontiers in Artificial Intelligence, Vol 7 (2024)
This research introduces a novel MOMENTS-SVD vector for fingerprint identification, combining invariant moments and SVD (Singular Value Decomposition), enhanced by a modified PCA (Principal Component Analysis). Our method extracts unique fingerprint
Externí odkaz:
https://doaj.org/article/1860d21f9db44eae9afcd1ba74af58e0
Autor:
Ali Bhar, Mounir Sayadi
Publikováno v:
Frontiers in Neurorobotics, Vol 18 (2024)
Unmanned Aerial Vehicles (UAVs) and quadrotors are being used in an increasing number of applications. The detection and management of forest fires is continually improved by the incorporation of new economical technologies in order to prevent ecolog
Externí odkaz:
https://doaj.org/article/a66bc65112c5459484efc5ac274d1828
Publikováno v:
IET Image Processing, Vol 15, Iss 3, Pp 634-647 (2021)
Abstract In recent decades, global warming has contributed to an increase in the number and intensity of wildfires destroying millions hectares of forest areas and causing many casualties each year. Firemen must therefore have the most effective mean
Externí odkaz:
https://doaj.org/article/ed2aa61e6c93494db16cf2a170f351d7
Autor:
Wafa Mbarki, Moez Bouchouicha, Sebastien Frizzi, Frederick Tshibasu, Leila Ben Farhat, Mounir Sayadi
Publikováno v:
Interdisciplinary Neurosurgery, Vol 22, Iss , Pp 100837- (2020)
Axial Lumbar disc herniation recognition is a difficult task to achieve, due to many challenges such as complex background, noise, blurry image. Lumbar discs are small joints that lie between each two vertebrae (L1-L2, L2-L3, L3-L4, L4-L5 and L5-S1).
Externí odkaz:
https://doaj.org/article/d60112cda3f241b197fba6bae6b5c8b4
Publikováno v:
Sensors, Vol 20, Iss 22, p 6429 (2020)
Forests provide various important things to human life. Fire is one of the main disasters in the world. Nowadays, the forest fire incidences endanger the ecosystem and destroy the native flora and fauna. This affects individual life, community and wi
Externí odkaz:
https://doaj.org/article/d575262fc9384b989d2eaefe845a817c
Publikováno v:
EURASIP Journal on Advances in Signal Processing, Vol 2010 (2010)
A novel method of colour image segmentation based on fuzzy homogeneity and data fusion techniques is presented. The general idea of mass function estimation in the Dempster-Shafer evidence theory of the histogram is extended to the homogeneity domain
Externí odkaz:
https://doaj.org/article/6591cac784ae485083699419c94f1b67
Publikováno v:
ELCVIA Electronic Letters on Computer Vision and Image Analysis, Vol 7, Iss 1 (2008)
In this paper, we propose a new nonlinear exponential adaptive two-dimensional (2-D) filter for texture characterization. The filter adaptive coefficients are updated with the Least Mean Square (LMS) algorithm. The proposed nonlinear model is used fo
Externí odkaz:
https://doaj.org/article/a5a598d140d144f89b7dd75e54d0bef9
Publikováno v:
Journal of X-Ray Science and Technology. 31:27-48
Computerized segmentation of brain tumor based on magnetic resonance imaging (MRI) data presents an important challenging act in computer vision. In image segmentation, numerous studies have explored the feasibility and advantages of employing deep n
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9f22600df86ea5546d8674fe60ad31a0
https://doi.org/10.3233/xst-221240
https://doi.org/10.3233/xst-221240