Optimized and autonomous machine learning framework for characterizing pores, particles, grains and grain boundaries in microstructural images

Grain structure control during metal 3D printing by high-intensity ultrasound

(2020) C. J. Todaro et al.   Nature Communications

Adaptive characterization of microstructure dataset using a two stage machine learning approach

(2020) Arun Baskaran et al.   COMPUTATIONAL MATERIALS SCIENCE

Automated Detection of Helium Bubbles in Irradiated X-750

(2020) Chris M. Anderson et al.   ULTRAMICROSCOPY

End-to-end Res-Unet based reconstruction algorithm for photoacoustic imaging

(2020) Jinchao Feng et al.   Biomedical Optics Express

Machine Learning-Based Classification of Dislocation Microstructures

(2019) Dominik Steinberger et al.   Frontiers in Materials

Residual neural network-based fully convolutional network for microstructure segmentation

(2019) Junmyoung Jang et al.   SCIENCE AND TECHNOLOGY OF WELDING AND JOINING

Deep Learning for Semantic Segmentation of Defects in Advanced STEM Images of Steels

(2019) Graham Roberts et al.   Scientific Reports

Relating porosity to fatigue failure in additively manufactured alloy 718

(2018) Luke Sheridan et al.   MATERIALS SCIENCE AND ENGINEERING A-STRUCTURAL MATERIALS PROPERTIES MICROSTRUCTURE AND PROCESSING

Selective laser melting of stainless steel and alumina composite: Experimental and simulation studies on processing parameters, microstructure and mechanical properties

(2018) Xinwei Li et al.   MATERIALS & DESIGN

Automated defect analysis in electron microscopic images

(2018) Wei Li et al.   npj Computational Materials

SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation

(2017) Vijay Badrinarayanan et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

The Influence of Porosity on Fatigue Crack Initiation in Additively Manufactured Titanium Components

(2017) S. Tammas-Williams et al.   Scientific Reports

Image driven machine learning methods for microstructure recognition

(2016) Aritra Chowdhury et al.   COMPUTATIONAL MATERIALS SCIENCE

Characterisation of local grain size variation of welded structural steel

(2016) Pauli Lehto et al.   Welding in the World

Permeability and strength of a porous metal structure fabricated by additive manufacturing

(2015) Tatsuaki Furumoto et al.   JOURNAL OF MATERIALS PROCESSING TECHNOLOGY

A facile method to determine pore size distribution in porous scaffold by using image processing

(2015) G. Lo Re et al.   MICRON

An automated simple algorithm for realistic pore network extraction from micro-tomography images

(2014) Arash Rabbani et al.   JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING

Characterization of Metal Powders Used for Additive Manufacturing

(2014) J. A. Slotwinski et al.   JOURNAL OF RESEARCH OF THE NATIONAL INSTITUTE OF STANDARDS AND TECHNOLOGY

Young’s modulus and volume porosity relationships for additive manufacturing applications

(2013) J. A. Choren et al.   JOURNAL OF MATERIALS SCIENCE

Influence of grain size distribution on the Hall–Petch relationship of welded structural steel

(2013) Pauli Lehto et al.   MATERIALS SCIENCE AND ENGINEERING A-STRUCTURAL MATERIALS PROPERTIES MICROSTRUCTURE AND PROCESSING

Development of porous medical implant scaffolds via laser additive manufacturing

(2012) Xu-bin SU et al.   TRANSACTIONS OF NONFERROUS METALS SOCIETY OF CHINA