In a bid to improve quality control and reduce production errors, manufacturers are increasingly adopting automated anomaly ...

North Dakota Agriculture Commissioner Doug Goehring has announced a $300,000 grant to fund a new drone-based weed detection project aimed at improving early identification of noxious weeds in soybean ...

In vehicular networks, the detection of malicious traffic presents significant challenges due to the critical nature of automotive systems and the evolving complexity of cyber attacks. This paper ...

We first benchmark the anomaly detection performance of three major visual frameworks-convolutional neural networks (CNNs), vision transformers (ViTs), and vision-language models (VLMs)-under varying ...

Anomaly detection (AD) of gearboxes is essential for ensuring the operational safety and reliability of the loader. However, identifying anomalies in non-stationary signals remains challenging as ...

Purpose: To evaluate the diagnostic accuracy of a deep learning autoencoder-based model utilizing regions of interest (ROI) from optical coherence tomography (OCT) texture enface images for detecting ...