GitHub

giacomobettas/anomaly-autoencoder-sklearn-baseline

Later iterations of the project (not in this repo) extended the idea with deep learning, data generators, YOLO-based person detection, and face recognition. This repository focuses deliberately on the ...
Visual Studio Magazine

Autoencoder Anomaly Detection Using PyTorch

Dr. James McCaffrey of Microsoft Research provides full code and step-by-step examples of anomaly detection, used to find items in a dataset that are different from the majority for tasks like ...
Visual Studio Magazine

Autoencoder Anomaly Detection Using PyTorch

The Data Science Lab Autoencoder Anomaly Detection Using PyTorch Dr. James McCaffrey of Microsoft Research provides full code and step-by-step examples of anomaly detection, used to find items in a ...
GitHub

Timeseries anomaly detection using an Autoencoder

It learns to encode data into a lower-dimensional representation and then decode it back to its original form. This process helps in tasks like dimensionality reduction, feature extraction, and ...
IEEE

Deep Learning Autoencoder based Anomaly Detection Model on 4G Network Performance Data

Abstract: A 4G network stands for a fourth-generation mobile network that enables 4G capable mobile phones to connect with the internet faster than ever. It is possible because of faster ...
IEEE

Multi-scale Autoencoder Suppression Strategy for Hyperspectral Image Anomaly Detection

Abstract: Autoencoders (AEs) have received extensive attention in hyperspectral anomaly detection (HAD) due to their capability to separate the background from the ...
Scientific Research Publishing

Intrusion Detection for Edge-IoT Using LSTM-Autoencoder ()

1 Laboratoire des Sciences Technologiques de l’Information et de la Communication (LASTIC), Ecole Supérieure Africaine des Technologie de l’Information et de la Communication (ESATIC), Abidjan, Côte d ...