A new study developed a snore-source classification model that uses STFT spectrograms, pretrained CNN features, and an L2-regularized SVM to identify where snoring originates in the upper airway.

A room-temperature quantum sensor captures tiny electrical changes and turns them into real-time energy-saving ...

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

The rising traffic density and heavier loads on the city’s vast network of bridges and highways have posed challenges to establishing an efficient and reliable inspection system for road safety.

Rob Sarno has been with the New York City’s Metropolitan Transportation Authority (MTA) for 14 years. As assistant chief track officer, he assists maintenance and emergency response — which also meant ...

This research investigates deep learning-based approach for defect detection in the steel production using Severstal steel dataset. The developed system integrates DenseNet121 for classification and ...

The stable operation of a power supply system is inseparable from the work of detecting defects in transmission lines. However, the insulator defect detection model based on deep learning is widely ...

Abstract: The use of Convolutional Neural Networks (CNN) for the application of wood defects detection has gained significant attention in recent years. In industrial settings, these tasks are ...