A novel fusion approach with a robust ParallelNet model for diabetic retinopathy diagnosis: H. Mahmood et al.
Published in: Pattern Analysis and Applications
Mar 21, 2025
Haroon Mahmood
Saad Ather
Aamir Wali
Arshad Ali
Tayyaba Gul Malik
Wardah Kafeel
Diabetic Retinopathy (DR) is a serious diabetes-related complication that can lead to significant retinal damage and irreversible vision loss if not detected and treated early. While numerous deep learning algorithms have recently been developed for DR diagnosis, however they often focus on specific symptoms like exudates, vessels, or hemorrhages, overlooking a comprehensive analysis of all relevant indicators. Though, previous studies have shown high performance on benchmark public datasets bu...
Improved Resilience of Image Encryption Based on Hybrid TEA and RSA Techniques
Published in: Tech Science Press
Mar 21, 2025
EBAO: An intrusion detection framework for wireless sensor networks using an enhanced binary Aquila Optimizer
Published in: Knowledge-Based Systems
Mar 15, 2025
Traditionally, Wireless Sensor Networks (WSNs) lack built-in algorithms to identify and react to intrusions and threats, necessitating the establishment of Intrusion Detection Systems (IDSs). In practice, it is difficult to design an IDS in WSNs due to the large scale, mobility, and limited memory of the sensors in WSNs. Feature Selection (FS) responds to these challenges by reducing data dimensionality and improving IDS accuracy, thereby enhancing intrusion detection classification by selectin...
Automated Authentication of Quranic Verses Using BERT (Bidirectional Encoder Representations from Transformers) based Language Models
Published in: Proceedings of the New Horizons in Computational Linguistics for Religious Texts
Mar 01, 2025
Khubaib Amjad Alam
Maryam Khalid
Syed Ahmed Ali
Haroon Mahmood
Qaisar Shafi
Muhammad Haroon
Zulqarnain Haider
The proliferation of Quranic content on digital platforms, including websites and social media, has brought about significant challenges in verifying the authenticity of Quranic verses. The inherent complexity of the Arabic language, with its rich morphology, syntax, and semantics, makes traditional text-processing techniques inadequate for robust authentication. This paper addresses this problem by leveraging state-of-the-art transformer-based Language models tailored for Arabic text processin...