This repository contains an end-to-end project demonstrating anomaly detection using two unsupervised machine learning algorithms: Isolation Forest and Local Outlier Factor (LOF). The project focuses ...
Abstract: Self supervised learning is emerging very fastly in computer vision tasks, which address the scarcity of annotated medical images. We introduce a self-supervised approach for anomaly ...
In this repository you will find a python implementation of our anomaly detection method, as well as explainability and feature selection techniques using SHAP and LIME XAI methods. Normalizing Flows ...