Startorus Fusion, a Chinese startup that leverages artificial intelligence (AI) to enhance fusion performance, has achieved ...

Dr. James McCaffrey presents a complete end-to-end demonstration of anomaly detection using k-means data clustering, implemented with JavaScript. Compared to other anomaly detection techniques, ...

Information and communication technology (ICT) is crucial for maintaining efficient communications, enhancing processes, and enabling digital transformation. As ICT becomes increasingly significant in ...

How can a small model learn to solve tasks it currently fails at, without rote imitation or relying on a correct rollout? A team of researchers from Google Cloud AI Research and UCLA have released a ...

1 Analytics Department, School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu, India 2 Department of Data Science, School of Computer Science and Engineering ...

Cloud infrastructure anomalies cause significant downtime and financial losses (estimated at $2.5 M/hour for major services). Traditional anomaly detection methods fail to capture complex dependencies ...

Abstract: Foetal anomaly detection is a critical task in prenatal care, requiring early diagnosis for appropriate medical intervention. However, the scarcity of annotated ultrasound data limits the ...

Welcome to the Open-Source Benchmark of Anomaly Detection (OSBAD) repository, a unified, reproducible framework for evaluating the performance of various statistical, distance-based, and machine ...

Traffic monitoring plays a vital role in smart city infrastructure, road safety, and urban planning. Traditional detection systems, including earlier deep learning models, often struggle with ...