Application of Deep Learning Workflow for Autonomous Grain Size Analysis
Published 2022 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Application of Deep Learning Workflow for Autonomous Grain Size Analysis
Authors
Keywords
-
Journal
MOLECULES
Volume 27, Issue 15, Pages 4826
Publisher
MDPI AG
Online
2022-07-29
DOI
10.3390/molecules27154826
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Defect Detection in Atomic Resolution Transmission Electron Microscopy Images Using Machine Learning
- (2021) Philip Cho et al. Mathematics
- Determination of the Grain Size in Single-Phase Materials by Edge Detection and Concatenation
- (2020) Lucijano Berus et al. Metals
- Using convolutional neural networks to predict composite properties beyond the elastic limit
- (2019) Charles Yang et al. MRS Communications
- Convolutional Neural Networks for Crystal Material Property Prediction Using Hybrid Orbital-Field Matrix and Magpie Descriptors
- (2019) Zhuo Cao et al. Crystals
- An automated methodology for grain segmentation and grain size measurement from optical micrographs
- (2019) Siddhartha Banerjee et al. MEASUREMENT
- Multi-channel convolutional neural networks for materials properties prediction
- (2019) Xiaolong Zheng et al. COMPUTATIONAL MATERIALS SCIENCE
- Automatic detection of particle size distribution by image analysis based on local adaptive canny edge detection and modified circular Hough transform
- (2018) Yingchao Meng et al. MICRON
- Weka Trainable Segmentation Plugin in ImageJ: A Semi-Automatic Tool Applied to Crystal Size Distributions of Microlites in Volcanic Rocks
- (2018) Charline Lormand et al. MICROSCOPY AND MICROANALYSIS
- U-Net: deep learning for cell counting, detection, and morphometry
- (2018) Thorsten Falk et al. NATURE METHODS
- Photovoltaic Performance of Perovskite Solar Cells with Different Grain Sizes
- (2015) Hyung Do Kim et al. ADVANCED MATERIALS
- Fast Edge Detection Using Structured Forests
- (2015) Piotr Dollar et al. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
- A Statistical Approach to Detect Edges in SAR Images Based on Square Successive Difference of Averages
- (2012) Xingyu Fu et al. IEEE Geoscience and Remote Sensing Letters
- Automatic grain size determination in microstructures using image processing
- (2012) H. Peregrina-Barreto et al. MEASUREMENT
- Comparison of EBSD and conventional methods of grain size measurement of hardmetals
- (2008) K.P. Mingard et al. INTERNATIONAL JOURNAL OF REFRACTORY METALS & HARD MATERIALS
- An elastic–viscoplastic model of deformation in nanocrystalline metals based on coupled mechanisms in grain boundaries and grain interiors
- (2007) Yujie Wei et al. MATERIALS SCIENCE AND ENGINEERING A-STRUCTURAL MATERIALS PROPERTIES MICROSTRUCTURE AND PROCESSING
Publish scientific posters with Peeref
Peeref publishes scientific posters from all research disciplines. Our Diamond Open Access policy means free access to content and no publication fees for authors.
Learn MoreCreate your own webinar
Interested in hosting your own webinar? Check the schedule and propose your idea to the Peeref Content Team.
Create Now