Digitalisation has rapidly changed the face of industry and business. Businesses have increasingly integrated modern technologies into their operations to improve real-time activity. However, ...

AI-based anomaly detection helps engineers identify potential problems early, to improve process efficiency, says Rachel ...

Scienaptic AI, a leading provider of AI-powered credit decisioning, announced today that CommunityWide Federal Credit Union has selected its platform to enhance real-time fraud and anomaly detection ...

We demonstrate the capabilities of our proposed anomaly detection method as a quality check for newly manufactured automotive transmissions. Given the use of frequency domain order-based features in ...

To advance intelligent manufacturing, sophisticated methods for high-quality process inspection are indispensable. This paper presents a systematic review of existing deep learning methodologies ...

Munir, M., Siddiqui, S.A., Dengel, A. and Ahmed, S. (2019) DeepAnT A Deep Learning Approach for Unsupervised Anomaly Detection in Time Series. IEEE Access, 7, 1991-2005.

Similarly, for disease detection, segmentation models such as U-Net and Mask R-CNN have been employed to localize affected areas, allowing for precise treatment. Beyond visual data, deep learning ...

Through advanced pattern recognition and anomaly detection, deep learning algorithms can detect intrusions and tampering attempts that conventional rule-based systems often miss.

This project intends to use deep learning technology to combine CNN with LSTM to establish a rapid forecast and anomaly detection method for weather radar echo signals, providing a new idea for radar ...