IEEE

Anomaly Detection Using Data-Driven Sparse Sensors: Combination of Modal Representation and Sensor Optimization for Sensing of Targeted Variable

Abstract: We propose an anomaly detection method based on modal representation and a noise-robust sparse sensor position optimization method. We focus on the detection of anomalies in global sea ...
SecurityWeek

ForceMemo: Python Repositories Compromised in GlassWorm Aftermath

Hackers use credentials stolen in the GlassWorm campaign to access GitHub accounts and inject malware into Python repositories.
IEEE

Anomaly Detection in Complex Systems Using Extended Isolation Forest and Denoising Autoencoder

Abstract: In this paper, we propose an anomaly detection model based on Extended Isolation Forest and Denoising Autoencoder, which achieves unsupervised anomaly detection with good generalization ...
InfoQ

Daggr Introduced as an Open-Source Python Library for Inspectable AI Workflows

A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...
Benzinga.com

Mastering the Earnings API: Earnings Calendars and Surprise Detection with Python

Earnings announcements are one of the few scheduled events that consistently move markets. Prices react not just to the reported numbers, but to how those numbers compare with expectations. A small ...
GitHub

The Numenta Anomaly Benchmark

The Numenta Anomaly Benchmark Welcome. This repository contains the data and scripts comprising the Numenta Anomaly Benchmark (NAB). NAB is a novel benchmark for evaluating algorithms for anomaly ...
Visual Studio Magazine

Anomaly Detection Using K-Means Clustering with JavaScript

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, ...
VentureBeat

AI coding transforms data engineering: How dltHub's open-source Python library helps developers create data pipelines for AI in minutes

Credit: Image generated by VentureBeat with FLUX-pro-1.1-ultra A quiet revolution is reshaping enterprise data engineering. Python developers are building production data pipelines in minutes using ...
GitHub

anomaly-segmentation

An anomaly detection library comprising state-of-the-art algorithms and features such as experiment management, hyper-parameter optimization, and edge inference.
Frontiers

HairSentinel: a time-aware anomaly detection framework for forecasting hairfall trends using temporal fusion transformers

Hairfall is a primary concern for many individuals worldwide today. Hair strands may fall due to various conditions such as hereditary factors, scalp health issues, nutritional deficiencies, hormonal ...
Scientific Research Publishing

Graph Neural Networks for Anomaly Detection in Cloud Infrastructure ()

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 ...