Litcius/Paper detail

Prediction of low-cycle fatigue crack development of sputtered Cu thin film using deep convolutional neural network

Michiaki Kamiyama, Kazuteru Shimizu, Yoshiaki AKINIWA

2022International Journal of Fatigue23 citationsDOIOpen Access PDF

Topics & Concepts

Convolutional neural networkReliability (semiconductor)Materials scienceElectrical resistance and conductanceThin filmFatigue testingParis' lawComposite materialStructural engineeringComputer scienceArtificial intelligenceFracture mechanicsCrack closureEngineeringNanotechnologyPhysicsQuantum mechanicsPower (physics)Non-Destructive Testing TechniquesInfrastructure Maintenance and MonitoringIndustrial Vision Systems and Defect Detection
Prediction of low-cycle fatigue crack development of sputtered Cu thin film using deep convolutional neural network | Litcius