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, ...
GitHub

ECG Anomaly Detection + Multi-Class Classification Using Autoencoder + XGBoost

ECG Signal (raw) │ Preprocessing - Standardization (Z-score normalization) - Trim length to be divisible by 8 - Reshape to (timesteps × 1 channel) │ 1D CNN Autoencoder ├── Encoder (Conv1D + MaxPooling ...
IEEE

Sample Similarity-Guided Spatial-Spectral Masked Autoencoder for Hyperspectral Anomaly Detection

Hyperspectral anomaly detection aims to identify targets that are significantly different from the surrounding background within hyperspectral image (HSI). The lack of prior information poses a ...
IEEE

Enhancing Microgrid Security: Web-Based Anomaly Detection Using Autoencoder

Microgrids provide a resilient and efficient alternative to traditional power grids, yet they remain vulnerable to operational anomalies, electrical faults, and cybersecurity threats. This study ...
GitHub

JuWanMaeng/Defect-Generation-Diffusion-Model

This environment is used for training and inference of our Stable Diffusion Inpainting-based anomaly generation model. GeoAware-SC is used to compute keypoint matches between normal and defective ...