ScienceDaily: Computers & Math News

Recent progress in camera systems, image analysis, and machine learning have made optical-based gesture recognition a more attractive option in most contexts. However, current methods are hindered by a variety of limitations, including high computational complexity, low speed, poor accuracy, or a low number of recognizable gestures.

Researchers have successfully applied machine learning to guide the synthesis of new nanomaterials, eliminating barriers associated with materials discovery. The highly trained algorithm combed through a defined dataset to accurately predict new structures that could fuel processes in clean energy, chemical and automotive industries.