Machine learning for morphable materials New platform can program the transformation of 2D stretchable surfaces into specific 3D shapes Date: January 12, 2022 ...

Washington University in St. Louis. "Machine learning generates 3D model from 2D pictures." ScienceDaily. ScienceDaily, 19 September 2022. <www.sciencedaily.com / releases / 2022 / 09 ...

This is explained by the importance of these newly synthesized materials, with applications ranging from energy to optics, electronics, catalysis, bio-detection, and structural materials. Advancing ...

BENGALURU: Researchers at the Indian Institute of Science (IISc) and University College London have developed a machine learning method to predict material properties using limited data.

A neural field network developed at Washington University in St. Louis, can create a continuous 3D model from a limited number of 2D images, and it does it without being trained on other samples.