Supervised methods of machine learning for email classification: a literature survey
Published in: Systems Science & Control Engineering
May 15, 2025
In today’s digital landscape, email is acknowledged as a critical conduit for global data exchanges. With a surge in data volume, malefactors exploit user identities, leading to data misuse. Cybercriminals employ electronic transgressions such as phishing and spam to orchestrate security infractions. Machine learning counters these breaches using myriad techniques, demonstrating significant efficiency in identifying phishing emails. We can divide machine learning into two types: supervised and ...
Robust Reversible Watermarking Technique Based on Improved Polar Harmonic Transform
Published in: Tech Science Press
May 06, 2025
Inheritance Modeling in Distributed Object-Oriented Design: An Extended G-Nets Model
Published in: TEM Journal
May 01, 2025
The emergence of an object-oriented paradigm has been beneficial for complex software development, and this paradigm has been used to develop architectures for distributed systems. Many object-oriented architectures have been suggested for developing object-based software, and several attempts have been made to specify object behaviors formally. Nevertheless, investigations into bridging the gap between object implementation and object formal models are limited. This paper presents a formal app...
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...