Dataset for: Deep learning and infrared thermography for asphalt pavement crack severity classification
<p>This is the dataset for the following paper: </p> <p>Fangyu Liu, Jian Liu, and Linbing Wang. "Deep learning and infrared thermography for asphalt pavement crack severity classification." Automation in Construction 140 (2022): 104383. https://doi.org/10.1016/j.autcon.2022.104383. </p> <p>Data component:</p> <ul> <li>01-Visible images: this folder includes fully visible images</li> <li>02-Infrared images: this folder includes fully infrared images</li> <li>03-Fusion(50IRT) images: this folder includes fusion images (50% infrared + 50% visible)</li> <li>04-Ground truth: this folder includes ground truth (txt files): <ul> <li>00-Label_meaning.txt: the meaning of label number</li> <li>01-All_label.txt: Image, label (severity level)</li> <li>02-Train_label.txt: the training set: Image, Label (severity level)</li> <li>02-Test_label.txt: the test set: Image, Label (severity level)</li> </ul> </li> </ul>
ShareScore
36/100
Overall dataset sharing score
Score breakdown
These five areas show where the dataset supports — or may limit — practical reuse.
- Stewardship
- 4
- Harmonization
- 8
- Access
- 16
- Reuse readiness
- 8
- Engagement
- 0