Principal Data Engineer Rajesh Mattaparthi is using transformer-based AI to detect hidden faults in standby power generators ...

Abstract: The continuously growing amount of monitored data in the Industry 4.0 context requires strong and reliable anomaly detection techniques. The advancement of Digital Twin technologies allows ...

Abstract: Weakly supervised video anomaly detection is a challenging problem due to the lack of frame-level labels in training videos. Most previous works typically tackle this task with the multiple ...

Atharv Kolhar, a staff test automation engineer at Figure AI, says the robotics industry needs a testing philosophy that ...

Attention-guided generator with dual discriminator GAN for real-time video anomaly detection 2024 J-EAAI Model Video anomaly detection guided by clustering learning 2024 J-PR Model Toward Video ...

These short anomaly-detection puzzles are designed to illustrate how reasoning often depends on identifying inconsistencies ...

One seismometer is often not enough to reliably detect earthquakes or human activity such as underground nuclear tests.

Artificial intelligence (AI) can put together readings from multiple sensors more effectively than classic technology, ...

Accurate RNA splicing is essential for gene expression and human health, yet predicting how DNA sequence variations affect ...

A new study explores deep learning for image-based defect detection during 3D printing, looking to catch bad builds.

The intersection of machine learning, biosensing technologies, and neurological behavior analysis presents fertile ground for groundbreaking research and innovation. This research topic aims to bridge ...