Month: April 2019

  • Robust Highway Lane Segmentation Based on LaneNet Trained BDD100K

    Robust Highway Lane Segmentation Based on LaneNet Trained BDD100K

    This is my final report of TensorFlow class at UCSC.

    Abstract

    In this report, we describe that how to prepare dataset and improve the performance of the CNN based lane segmentation by using transfer learning. In addition, we evaluate and compare four types of the methods for lanes segmentation such as the simple rule based method, the CNN based method trained with daytime dataset, the CNN trained daytime dataset filtered gamma correction, and the CNN trained high diversity road dataset.


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