Automated machine learning (AutoML) is a generic term for a specific approach to machine
learning (ML) area that tries to automate the end-to-end process of employing repetitive ML …

As the alarming growth of computer connectivity and the significant number of computer-
related applications increased lately, the challenge of achieving cyber-security has become …

The escalating frequency and sophistication of cyber threats pose significant challenges to
traditional intrusion detection methods. Signature-based misuse detection, hybrid detection …

Slope instability can lead to catastrophic consequences. However, predicting slope stability
effectively is still challenging because of the complex mechanisms and multiple influencing …

Machine learning algorithms present a robust alternative for building Intrusion Detection
Systems due to their ability to recognize attacks in computer network traffic by recognizing …

The stability of underground entry-type excavations (UETEs) is of paramount importance for
ensuring the safety of mining operations. As more engineering cases are accumulated …

Urban forest surveillance relies on several aspects that involve the analysis of green area
preservation and the monitoring of individual trees. Urban trees are essential to maintain the …

The task of ensuring cyber-security has grown increasingly challenging given the
concerning expansion of Computing connection and furthermore, there are a large number …

The task of ensuring cyber-security has grown increasingly challenging as the alarming
expansion of computer connectivity and the large number of computer-related applications …