Kamilov et al. use machine-learning algorithms — computer programs that can learn from and make predictions based on input data — to give a boost to 3D phase imaging. By doing so, the authors ...

Therefore, 3D printing is a powerful tool to create physical models which might provide a well-characterized training dataset as a purpose-built surrogate to clinical data for machine learning.

These building blocks, which in this case are composed of carbon, are arranged in complex 3D ... data; it learned from what changes to the shapes worked and what didn’t, enabling it to predict ...

We propose two different 3D-Hybrid Convolutional Autoencoder models with increased compression rates compared to 1D methods that can compress ... understanding the strengths and limitations of machine ...

Today is possible to extract features specific to various fields of application with the application of modern machine learning techniques ... using Sentinel-2 satellite data; (2) Publications ...

The framework models the complex mechanical behavior of spinodal microstructures by combining submicron 3D printing ... Most approaches to machine learning-based inverse design require large amounts ...