A high-performance AI framework enhances anomaly detection in industrial systems using optimized Graph Deviation Networks and graph attention ...

In a recent study, a research team from Chung-Ang University, Korea presents open research questions related to anomaly detection using deep learning and curates open-access time series datasets, an ...

Anomaly detection in images is rapidly emerging as a critical field in both industrial quality control and medical diagnostics. Leveraging deep learning techniques, researchers have developed ...

Imagimob AI, a development platform for building tinyML applications for edge devices, adds support for deep learning anomaly detection. Deep anomaly detection—the identification of rare items, events ...

Dr. James McCaffrey from Microsoft Research presents a complete program that uses the Python language LightGBM system to create a custom autoencoder for data anomaly detection. You can easily adapt ...

In this study, we explore an image-based method to automate the manual anomaly detection process on quality control plots using deep learning. To do this we trained a Convolutional Neural Network (CNN ...

COVAD: Content-oriented video anomaly detection using a self attention-based deep learning model Peer-Reviewed Publication Beijing Zhongke Journal Publising Co. Ltd.

This article explores the transformative potential of machine learning algorithms in combating supply chain fraud, focusing on techniques such as supervised and unsupervised learning, anomaly ...