Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Hanadi Hassen Mohammed"'
Autor:
Najmath Ottakath, Somaya Al-Maadeed, Susu M. Zughaier, Omar Elharrouss, Hanadi Hassen Mohammed, Muhammad E. H. Chowdhury, Ahmed Bouridane
Publikováno v:
Diagnostics, Vol 13, Iss 15, p 2614 (2023)
The carotid artery is a major blood vessel that supplies blood to the brain. Plaque buildup in the arteries can lead to cardiovascular diseases such as atherosclerosis, stroke, ruptured arteries, and even death. Both invasive and non-invasive methods
Externí odkaz:
https://doaj.org/article/a0cceb485fbe484c981f95303abf47bd
Publikováno v:
IET Image Processing, Vol 15, Iss 10, Pp 2332-2341 (2021)
Abstract Word spotting on degraded and noisy historical documents can become a challenging task considering the computational time and memory usage required to scan the entire document image. This paper proposes a new effective technique for multi‐
Externí odkaz:
https://doaj.org/article/729a08cb3a2b48bca596e742a6ce5e7a
Autor:
Hanadi Hassen Mohammed, Omar Elharrouss, Najmath Ottakath, Somaya Al-Maadeed, Muhammad E. H. Chowdhury, Ahmed Bouridane, Susu M. Zughaier
Publikováno v:
Applied Sciences, Vol 13, Iss 8, p 4821 (2023)
Common carotid intima-media thickness (CIMT) is a common measure of atherosclerosis, often assessed through carotid ultrasound images. However, the use of deep learning methods for medical image analysis, segmentation and CIMT measurement in these im
Externí odkaz:
https://doaj.org/article/d9f41c569e5348f586f087cef7635761
WSNet – Convolutional Neural Networkbased Word Spotting for Arabic and English Handwritten Documents
Publikováno v:
TEM Journal. :264-271
This paper proposes a new convolutional neural network architecture to tackle the problem of word spotting in handwritten documents. A Deep learning approach using a novel Convolutional Neural Network is developed for the recognition of the words in
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5c7da06b074e63be6773c3987b3db0f5
https://doi.org/10.18421/tem111-33
https://doi.org/10.18421/tem111-33
Publikováno v:
IET Image Processing, Vol 15, Iss 10, Pp 2332-2341 (2021)
Word spotting on degraded and noisy historical documents can become a challenging task considering the computational time and memory usage required to scan the entire document image. This paper proposes a new effective technique for multi‐language
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::90f9045dbc234f899cff1e289ffa2b75
https://doi.org/10.1049/ipr2.12216
https://doi.org/10.1049/ipr2.12216
Deep Convolutional Neural Networks (CNNs) have recently reached state-of-the-art Handwritten Text Recognition (HTR) performance. However, recent research has shown that typical CNNs' learning performance is limited since they are homogeneous networks
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5dbb9ca8b2c0de44420e9422c63c7192
