Zobrazeno 1 - 10
of 71
pro vyhledávání: '"Mohammed Al Sarem"'
Publikováno v:
Alexandria Engineering Journal, Vol 111, Iss , Pp 540-554 (2025)
Social media platforms, such as Facebook and X (formally known as Twitter), have become indispensable tools in today's society because they facilitate social discussion and information sharing. This feature makes social networks more attractive for s
Externí odkaz:
https://doaj.org/article/5a7ae3bf0aa24c90844d6d1836fbca23
Autor:
Merouane Boudraa, Akram Bennour, Tahar Mekhaznia, Abdulrahman Alqarafi, Rashiq Rafiq Marie, Mohammed Al-Sarem, Ayush Dogra
Publikováno v:
Acta Informatica Pragensia, Vol 13, Iss 2, Pp 251-272 (2024)
The automated classification of historical document scripts holds profound implications for historians, providing unprecedented insights into the contexts of ancient manuscripts. This study introduces a robust deep learning system integrating an inte
Externí odkaz:
https://doaj.org/article/8dfd47e0274140a087f71ad6ba9a0125
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-12 (2024)
Abstract Recent studies have shown that dental implants have high long-term survival rates, indicating their effectiveness compared to other treatments. However, there is still a concern regarding treatment failure. Deep learning methods, specificall
Externí odkaz:
https://doaj.org/article/78ff00dd82c04684a462cefe07d5e833
Autor:
Yousra Hadhoud, Tahar Mekhaznia, Akram Bennour, Mohamed Amroune, Neesrin Ali Kurdi, Abdulaziz Hadi Aborujilah, Mohammed Al-Sarem
Publikováno v:
Diagnostics, Vol 14, Iss 23, p 2754 (2024)
Background/Objectives: Chest disease identification for Tuberculosis and Pneumonia diseases presents diagnostic challenges due to overlapping radiographic features and the limited availability of expert radiologists, especially in developing countrie
Externí odkaz:
https://doaj.org/article/f5df6691ecaf41cb808b05d5561b3c60
Publikováno v:
Diagnostics, Vol 14, Iss 23, p 2655 (2024)
Background/Objectives: In contrast to traditional biometric modalities, such as facial recognition, fingerprints, and iris scans or even DNA, the research orientation towards chest X-ray recognition has been spurred by its remarkable recognition rate
Externí odkaz:
https://doaj.org/article/1734784423b346a6981cbdc14295faf3
Autor:
Mujeeb Ur Rehman, Arslan Shafique, Kashif Hesham Khan, Saad Nasser Altamimi, Sultan Noman Qasem, Mohammed Al-Sarem
Publikováno v:
IEEE Access, Vol 12, Pp 17926-17944 (2024)
In the era of big data, protecting digital images from cyberattacks during network transmission is of utmost importance. While various image encryption algorithms have been developed, some remain vulnerable to specific cyber threats. This paper prese
Externí odkaz:
https://doaj.org/article/0c586bb468e14435bc4fea1b43a75186
Publikováno v:
PeerJ Computer Science, Vol 10, p e1792 (2024)
This article introduces the Social-Emotional Nurturing and Skill Enhancement System (SENSES-ASD) as an innovative method for assisting individuals with autism spectrum disorder (ASD). Leveraging deep learning technologies, specifically convolutional
Externí odkaz:
https://doaj.org/article/5f6c0a2a5cf247fcaa09522a07f6428a
Publikováno v:
IEEE Access, Vol 11, Pp 89694-89710 (2023)
The recent increase in credit card fraud is rapidly has caused huge monetary losses for individuals and financial institutions. Most credit card frauds are conducted online by illegally obtaining payment credentials through data breaches, phishing, o
Externí odkaz:
https://doaj.org/article/46b3cda7941041c29da7ba3e00759e65
Autor:
Rajat Mehrrotraa, M. A. Ansari, Rajeev Agrawal, Pragati Tripathi, Md Belal Bin Heyat, Mohammed Al-Sarem, Abdullah Yahya Mohammed Muaad, Wamda Abdelrahman Elhag Nagmeldin, Abdelzahir Abdelmaboud, Faisal Saeed
Publikováno v:
IEEE Access, Vol 10, Pp 85442-85458 (2022)
Tuberculosis (TB) is a communicable pulmonary disorder and countries with low and middle-income share a higher TB burden as compared to others. The year 2020–2021 universally saw a brutal pandemic in the form of COVID-19, that crushed various lives
Externí odkaz:
https://doaj.org/article/51b23e2fb07f4da0953f15bb9a6317e1
Autor:
Bander Ali Saleh Al-rimy, Faisal Saeed, Mohammed Al-Sarem, Abdullah M. Albarrak, Sultan Noman Qasem
Publikováno v:
Diagnostics, Vol 13, Iss 11, p 1903 (2023)
Knee osteoarthritis (OA) detection is an important area of research in health informatics that aims to improve the accuracy of diagnosing this debilitating condition. In this paper, we investigate the ability of DenseNet169, a deep convolutional neur
Externí odkaz:
https://doaj.org/article/75a1c675ad164d178b0ecda709adf7f6