Automation that actually understands your homelab.

Abstract: Autoencoder (AE) is extensively utilized in hyperspectral anomaly detection (HAD) tasks owing to its robust feature extraction and image reconstruction capabilities. However, AE lacks ...

Real-time detection of anomalies in data streams is a foundation of modern applied analysis in complex systems. It enables experts to design rapid, efficient, reliable, and high-performance decision ...

Horror games are one of the best genres on Roblox, but the amount of jumpscares Scary Shawarma Kiosk the Anomaly brings is amazing. The game lets you run a shawarma shop while finding anomalies and ...

Abstract: Unsupervised medical anomaly detection aims to identify abnormal images by training exclusively on normal samples, thereby enabling the detection of disease related irregularities without ...

A complete end-to-end Streaming Data Analytics (SDA) project that generates real-time weather data, applies SDA filters (Moving Average, EWMA), detects anomalies using Isolation Forest, and visualizes ...

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?

This repository contains an end-to-end MLOps project that builds, tests, and containerizes a real-time anomaly detection API using time-series data. The Numenta Anomaly Benchmark (NAB) dataset is used ...

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 ...

Intrusion detection systems (IDS) and anomaly detection techniques are critical components of modern cybersecurity, enabling the identification of malicious activities and system irregularities in ...