Collaborative Learning of Anomalies with Privacy (CLAP) for Unsupervised Video Anomaly Detection: A New Baseline

1 code implementation • 1 Apr 2024 • Anas Al-lahham, Muhammad Zaigham Zaheer, Nurbek Tastan, Karthik Nandakumar

Unsupervised (US) video anomaly detection (VAD) in surveillance applications is gaining more popularity recently due to its practical real-world applications.

Anomaly Detection Privacy Preserving +1

A Coarse-to-Fine Pseudo-Labeling (C2FPL) Framework for Unsupervised Video Anomaly Detection

1 code implementation • 26 Oct 2023 • Anas Al-lahham, Nurbek Tastan, Zaigham Zaheer, Karthik Nandakumar

Video anomaly detection (VAD) is well-studied in the one-class classification (OCC) and weakly supervised (WS) settings.

One-Class Classification Pseudo Label +1

Sky Imager-Based Forecast of Solar Irradiance Using Machine Learning

no code implementations • 26 Oct 2023 • Anas Al-lahham, Obaidah Theeb, Khaled Elalem, Tariq A. Alshawi, Saleh A. Alshebeili

Ahead-of-time forecasting of the output power of power plants is essential for the stability of the electricity grid and ensuring uninterrupted service.