Isolation Forest detects anomalies by isolating observations. It builds binary trees (called iTrees) by recursively ...

Data quality significantly impacts the results of data analytics. Researchers have proposed machine learning based anomaly detection techniques to identify incorrect data. Existing approaches fail to ...

The reconstruction loss of the trained LSTM Autoencoder model is estimated for the up-to-date reliability streaming data, and the result is used to infer MEC services’ runtime reliability anomalies.

An unsupervised autoencoder approach achieves moderate success for anomaly detection (accuracy = 0.881) but struggles with recall (0.070). These findings highlight the trade-off between detection ...

Open Public Test Submission Release anonymized images Release training code and checkpoints Release code for points projection to images Release the data Release evaluation code As of June 14, 2025, ...

It integrates accident detection and damage classification using YOLOv8 for accident detection and a Convolutional Neural Network (CNN) for damage classification. Real-time accident detection from ...