Deep learning based vision for driverless vehicles in hazy environmental conditions

Cameron Hodges

Research output: ThesisMaster's Thesis

215 Downloads (Pure)

Abstract

Technology and automotive companies have contributed ever increasing resources to the aim of developing self-driving or fully autonomous vehicles. While traditional robotics techniques provided initial successes in this area, machine learning and deep learning have become a critical technology for the further development in this area. Specifically, in the area of machine vision, there is a need for designing a robust object detection system with respect to negative environmental conditions such as haze. Therefore, I have created a novel training method for a deep learning based dehazing model that provides superior performance when compared to existing methods.
Original languageEnglish
QualificationMasters
Awarding Institution
  • The University of Western Australia
Supervisors/Advisors
  • Bennamoun, Mohammed, Supervisor
  • Rahmani, Hossein, Supervisor
  • An, Senjian, Supervisor
  • Boussaid, Farid, Supervisor
Award date29 Sep 2021
DOIs
Publication statusUnpublished - 2021

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