Principal Data Engineer Rajesh Mattaparthi is using transformer-based AI to detect hidden faults in standby power generators ...

Demonstrating academic excellence and a strong interest in AI-related domains, seven students of Computer Science Engineering ...

By Dr. Richmond Atuahene1.0 Introduction/ BackgroundGlobalization and digitization are two major trends that will shape the future of nations. Despite the many challenges associated with adapting to ...

Google Cloud has expanded its enterprise cybersecurity push with AI Threat Defense, as the market shifts towards AI-native threat detection, contextual triage, and supervised remediation. The launch ...

Abstract: Efficiently detecting anomalies in spacecraft data poses a significant challenge in modern space missions. We introduce Spacecraft Anomaly Detection using Deep Learning (SADDLE), a novel ...

A professionally curated list of awesome resources (paper, code, data, etc.) on Deep Graph Anomaly Detection (DGAD), which is the first work to comprehensively and systematically summarize the recent ...

In this era of digital transformation, buzzwords like ‘Industry 4.0’ and ‘digitalization’ have become part of our daily vocabulary. But behind these trendy terms lies a potent technological innovation ...

AI security cameras are transforming modern smart home security by analyzing live video feeds in real time to detect unusual activity with high accuracy. Using advanced convolutional neural networks, ...

5.1 RQ1: How does our proposed anomaly detection model perform compared to the baselines? 5.2 RQ2: How much does the sequential and temporal information within log sequences affect anomaly detection?

The proposed method employs a thresholded pixel-wise difference between reconstructed image and input image to localize anomaly. The threshold is determined by first using a subset of anomalous-free ...