Road Segmentation with Neural Networks

Document Type

Article

Authors

Tsz Hong Andy Lau, University of Minnesota, MorrisFollow

Abstract

Autonomous driving is the next biggest technological advance in the automobile industry. However, the current technology is still very much in its infancy. Networks of sensors such as cameras and LIDAR systems are used to record and measure the road condition. While neural networks are used to understand the road condition and make the correct decision to drive the vehicle. In this paper, we are specifically focusing on the road segmentation of autonomous vehicle technology. We will be going over the two approaches to road segmentation by Oliveira, et al [5] and Caltagirone, et al [2], and we will compare the performance of each approach on a road benchmark dataset called KITTI dataset.

Recommended Citation

Lau, Tsz Hong Andy (2018) "Road Segmentation with Neural Networks," Scholarly Horizons: University of Minnesota, Morris Undergraduate Journal: Vol. 5: Iss. 2, Article 5.
DOI: https://doi.org/10.61366/2576-2176.1061
Available at: https://digitalcommons.morris.umn.edu/horizons/vol5/iss2/5

Primo Type

Article