A machine learning model has been developed that makes optical spectroscopy data easier and quicker to interpret. Researchers from Rice University (TX, USA) have developed a new machine learning ...

Hyperspectral imaging (HSI) has emerged as a pivotal non‐destructive analytical tool by capturing both spatial and spectral information of food products. This technique enables the identification and ...

A research team has developed a new hybrid artificial intelligence framework that can accurately estimate leaf nitrogen content without relying on labor-intensive field measurements.

Many techniques in computational materials science require scientists to identify the right set of parameters that capture the physics of the specific material they are studying. Calculating these ...

A research team demonstrates that hyperspectral sensing, combined with advanced artificial intelligence, can accurately estimate multiple biochemical and mineral traits in grapevine leaves at once.

Chemists have created a machine learning tool that can identify the chemical composition of dried salt solutions from an image with 99% accuracy. By using robotics to prepare thousands of samples and ...