Recognition of Traffic Congestion State using a Deep Convolutional Network

Abstract This paper describes a two-phase deep learned neural network for the recognition of traffic congestion in surveillance camera imagery. The network is transfer-learned using GoogLeNet for image processing and a bespoke subnet for congestion recognition.
  • Chris Willis (BAE)
  • Dan Harborne (Cardiff)
  • Richard Tomsett (IBM UK)
  • Moustafa Alzantot (UCLA)
Date Sep-2017
Venue 1st Annual Fall Meeting of the DAIS ITA, 2017