Corrosion Condition State Semantic Segmentation Dataset

<p>The data was collected from the Virginia Department of
Transportation (VDOT) Bridge Inspection Reports. The data was semantically
annotated following the corrosion condition state guidelines stated in the
American Association of State Highway and Transportation Officials (AASHTO) and
Bridge Inspector's Reference Manual (BIRM). There were four corrosion class
categories: [good, fair, poor, severe]. The dataset consisted of 440 finely
annotated images and was randomly split into 396 training images and 44 testing
images. The images were resized to 512x512 for training and testing the
DeeplabV3+ model. The original and resized images are included. After training
with the DeeplabV3+ model (DOI: 10.7294/16628668), we were able to receive an
F1 score of 86.67. More details of the training, the results, the dataset, and
the code may be referenced in the journal article. The GitHub repository
information may be found in the journal article.</p><p><br>If you are using the dataset in your work, please include <b>both </b>the journal article and the dataset citation. <br></p>