Deep learning for synthetic microstructure generation in a materials-by-design framework for heterogeneous energetic materials

5 April 2020

Papers citing "Deep learning for synthetic microstructure generation in a materials-by-design framework for heterogeneous energetic materials"

5 / 5 papers shown

Title
Synthetic dual image generation for reduction of labeling efforts in semantic segmentation of micrographs with a customized metric function Matias Oscar Volman Stern Dominic Hohs Markos Diomataris Michael J. Black Gerhard Schneider DiffM 29 0 0 01 Aug 2024
Deep Learning of Crystalline Defects from TEM images: A Solution for the Problem of "Never Enough Training Data" Kishan Govind D. Oliveros A. Dlouhý M. Legros Stefan Sandfeld 18 8 0 12 Jul 2023
A physics-aware deep learning model for energy localization in multiscale shock-to-detonation simulations of heterogeneous energetic materials Phong C. H. Nguyen Y. Nguyen P. Seshadri Joseph B. Choi H. Udaykumar Stephen Seung-Yeob Baek AI4CE 9 18 0 08 Nov 2022
PARC: Physics-Aware Recurrent Convolutional Neural Networks to Assimilate Meso-scale Reactive Mechanics of Energetic Materials Phong C. H. Nguyen Y. Nguyen Joseph B. Choi P. Seshadri H. Udaykumar Stephen Seung-Yeob Baek AI4CE 16 16 0 04 Apr 2022
A Style-Based Generator Architecture for Generative Adversarial Networks Tero Karras S. Laine Timo Aila 264 10,348 0 12 Dec 2018