Deep Learning Identifies Wet Road Hazards From Sound Input (thestack.com)

An anonymous reader writes: Researches have used recurrent neural network architecture to develop an audio-interpretation system that can understand how wet a road is, using techniques more commonly employed in speech recognition and music analysis. Every year 384,032 persons are injured and 4,789 persons killed through wet roads, and it's a problem that also threatens to hamper the usefulness of self-driving cars, which are likely to either become dangerous or prohibitively cautious in the absence of good information about the safety of road surfaces.