A novel machine learning based method to compress and reconstruct 3D spatial data from remote sensing
Land surveys are used to find and monitor land features in large areas. Information such as differences in elevation, area and heights of buildings, vegetation, water and roads can be gathered by physically surveying the land. The same information can be gathered using pictures captured remotely by cameras mounted on satellites or tripods, drones and helicopters.
Researchers develop a new AI-powered algorithm that significantly improves the energy efficiency of a wirelessly powered communication network.
Radio Frequency (RF) signals are electromagnetic radiations used in wireless communication. RF signals transmit information and carry an inherent small electrical energy component. Emerging technology harvests this electrical energy and powers many wireless devices (called nodes) over a wide area, such as medical implants or IoTs.
Scientists have devised a novel approach to combine memory and computation units
Modern computers carry out computations — also called ‘logical operations’ — on massive amounts of data that are stored in specialised memory devices. The computing blocks need to exchange significant amounts of data with Random Access Memory, or RAM, a type of temporary memory. Over the years, various applications that search and process the appropriate data from memory devices have increasingly demanded faster computations.