Augmenting an existing raveling dataset with controlled variations in data size, illumination, and spatial position improves detection model accuracy by at least 9.2 percent and produces more consistent results across multiple years of real road data.
Miller and William Y
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Towards Successful Implementation of Automated Raveling Detection: Effects of Training Data Size, Illumination Difference, and Spatial Shift
Augmenting an existing raveling dataset with controlled variations in data size, illumination, and spatial position improves detection model accuracy by at least 9.2 percent and produces more consistent results across multiple years of real road data.