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Found 3 papers, 1 papers with code
A generalized machine learning framework for brittle crack problems using transfer learning and graph neural networks
The new framework, ACCelerated Universal fRAcTure Emulator (ACCURATE), is generalized to a variety of crack problems by using a sequence of TL update steps including (i) arbitrary crack lengths, (ii) arbitrary crack orientations, (iii) square domains, (iv) horizontal domains, and (v) shear loadings.
Shedding some light on Light Up with Artificial Intelligence
This project is an effort to apply new AI techniques for solving the Light-up puzzle faster and more computationally efficient.
Optimized and autonomous machine learning framework for characterizing pores, particles, grains and grain boundaries in microstructural images
For GBs, another optimized CEDN was developed to generate RGB segmentation images, which were used to obtain grain size distribution using two regression CNNS.
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