Despite advances in machine vision, processing visual data requires substantial computing resources and energy, limiting deployment in edge devices. Now, researchers from Japan have developed a self-powered artificial synapse that distinguishes colors with high resolution across the visible spectrum, approaching human eye capabilities. The device, which integrates dye-sensitized solar cells, generates its electricity and can perform complex logic operations without additional circuitry, paving the way for capable computer vision systems integrated in everyday devices.
Read more …Self-powered artificial synapse mimics human color vision
Researchers have discovered that the mixing of small particles between two solid electrolytes can generate an effect called a 'space charge layer,' an accumulation of electric charge at the interface between the two materials. The finding could aid the development of batteries with solid electrolytes, called solid-state batteries, for applications including mobile devices and electric vehicles.
Read more …Discovery could boost solid-state battery performance
A team led by Virginia Tech graduate student Samuel Daramola developed a deep learning model called LSTM-SAM that predicts extreme water levels from tropical cyclones more efficiently and accurately, especially in data-scarce coastal regions, to offer a faster, low-cost tool for flood forecasting.
Read more …Researchers use deep learning to predict flooding this hurricane season