Abstract: Anomaly detection for time-series data has been viewed widely in many practical applications and caused lots of research interests. A popular solution based on deep learning techniques is ...

Abstract: In recent years, tensor decomposition-based approaches for hyperspectral anomaly detection (HAD) have gained significant attention in the field of remote sensing. However, existing methods ...

We’re mere days away from mysterious interstellar object 3I/ATLAS making its closest approach to Earth before it speeds back out of the solar system, never to be seen again. The object, which ...

Learn how to use Premiere Pro’s Scene Edit Detection feature to automatically detect cuts in any video. This tutorial shows how to speed up your workflow, save time, and quickly break down footage for ...

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, ...

T.J. Thomson receives funding from the Australian Research Council. He is an affiliate with the ARC Centre of Excellence for Automated Decision Making & Society. Aaron J. Snoswell receives research ...

ClickFix attacks have evolved to feature videos that guide victims through the self-infection process, a timer to pressure targets into taking risky actions, and automatic detection of the operating ...

A rift anomaly in The Outer Worlds 2 is a unique cosmic event, and, although they are quite deadly for you to close, they're full of hidden treasures. The only way to open a rift anomaly is by using ...

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?

ABSTRACT: Purpose: The purpose of this study is to develop a scalable, risk-aware artificial intelligence (AI) framework capable of detecting financial fraud in high-throughput digital transaction ...