Automated Quantitative Analyses of Fatigue-Induced Surface Damage by Deep Learning

Micromechanical Modelling of the Influence of Strain Ratio on Fatigue Crack Initiation in a Martensitic Steel-A Comparison of Different Fatigue Indicator Parameters

(2019) Benjamin Josef Schäfer et al.   Materials

DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs

(2018) Liang-Chieh Chen et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

Quantitative investigation of micro slip and localization in polycrystalline materials under uniaxial tension

(2018) Zhen Zhang et al.   INTERNATIONAL JOURNAL OF PLASTICITY

Advanced Steel Microstructural Classification by Deep Learning Methods

(2018) Seyed Majid Azimi et al.   Scientific Reports

A High Resolution Digital Image Correlation Study under Multiaxial Loading

(2018) E. Polatidis et al.   EXPERIMENTAL MECHANICS

Crystal plasticity modelling and HR-DIC measurement of slip activation and strain localization in single and oligo-crystal Ni alloys under fatigue

(2017) Yongjun Guan et al.   INTERNATIONAL JOURNAL OF PLASTICITY

Small-Scale Multiaxial Setup for Damage Detection Into the Very High Cycle Fatigue Regime

(2015) T. Straub et al.   EXPERIMENTAL MECHANICS

Implementation and verification of a microstructure-based capability for modeling microcrack nucleation in LSHR at room temperature

(2015) Albert Cerrone et al.   MODELLING AND SIMULATION IN MATERIALS SCIENCE AND ENGINEERING

The Pascal Visual Object Classes Challenge: A Retrospective

(2014) Mark Everingham et al.   INTERNATIONAL JOURNAL OF COMPUTER VISION

The physics of fatigue crack initiation

(2012) Michael D. Sangid   INTERNATIONAL JOURNAL OF FATIGUE

A theory of learning from different domains

(2009) Shai Ben-David et al.   MACHINE LEARNING

Extrusions and intrusions in fatigued metals. Part 1. State of the art and history†

(2009) J. Man et al.   PHILOSOPHICAL MAGAZINE