It is a challenging task to accurately segment damaged road markings from images, mainly
due to their fragmented, dense, small-scale, and blurry nature. This study proposes a multi …

Malware is becoming increasingly sophisticated, with new malware constantly emerging,
posing challenges for cybersecurity teams to classify them accurately. Traditional supervised …

The paper introduces the BioSentinel Neural Network (BSNN), a novel hybrid deep learning
model designed to enhance malware detection, particularly focusing on zero-day threats …

Visualization-based malware detection gets more and more attention for detecting
sophisticated malware that traditional antivirus software may miss. The approach involves …

Nowadays, almost everyone can shoot numerous Macrophotography Images (MPI) using
mobile phone camera, which can automatically meet the aesthetics needs, and meanwhile …

In the rapidly evolving landscape of cyber security, the incessant advancement of malicious
activities presents a formidable challenge, necessitating a paradigm shift in detection …

Preventing malware attacks is crucial, as they can lead to financial losses, privacy breaches,
system downtime, and reputational damage. Various machine learning and deep learning …