Complementing human expert in perceptual and cognitive decision making

Identifying objects in remote sensing data is a challenging task that requires highly skilled and costly human experts to analyze massive amount of digital data.  Neurala has realized a remote sensing software platform for the purpose of developing automatic methods to delineate water flow and soil loss from LIDAR data. The application of bio-inspired machine vision and classification algorithms is key to accurately and quickly process large amount of remote sensing data, extracting knowledge that is then applied to make better and faster decision in soil conservation practices.

Benefits: Automatic flow-delineation techniques realize consistent savings in terms of decision time and cost of land surveys by human experts.

Demos: coming soon!