Browse Items (5 total)

AbstractThis study addresses the escalating challenge of Twitter spam detection by leveraging the power of Convolutional Neural Networks (CNNs). With the proliferation of spam content on social media platforms, traditional machine…

This study identified ransomware threats in social media platforms by evaluating the performance of Assessing different machine-learning algorithms in various aspects of detecting and classifying ransomware content. The primary problem …

Small datasets and imbalanced classes often cause problems when used as primary research material. In the case of classification and object detection, some researchers proposed Transfer Learning (TF) with several frozen layers. …

This study focuses on using machine learning algorithms to detect cardiovascular diseases, addressing the critical need for accurate and timely diagnosis of these conditions, which are significant contributors to global morbidity and mortality. The…

n the realm of computer network security, the role of intrusion detection is crucial for safeguarding systems against various threats. However, with the advancement of intrusion techniques, traditional detection methods have…