3DIFICE: A Synthetic Dataset for Training Computer Vision Algorithms to Recognize Earthquake Damage to Reinforced Concrete Structures
Dataset Description |
3DIFICE: 3-dimensional Damage Imposed on Frame structures for Investigating Computer vision-based Evaluation methods This dataset contains 1,396 synthetic images and label maps with various types of earthquake damage imposed on reinforced concrete frame structures. Damage includes: cracking, spalling, exposed transverse rebar, and exposed longitudinal rebar. Each image has an associated label map that can be used for training machine learning algorithms to recognize the various types of damage. |
Subject |
Technology and Engineering |
Keywords |
computer vision; earthquake engineering; structural health monitoring; civil engineering; structural engineering; |
License |
CC BY |
Corresponding Creator |
Nathaniel Levine |
Downloaded |
519 times |
| Version | DOI | Comment | Publication Date |
|---|---|---|---|
| 1 | 10.13012/B2IDB-6415287_V1 | 2022-09-29 |
Contact the Research Data Service for help interpreting this log.
| RelatedMaterial | destroy: {"material_type"=>"", "availability"=>nil, "link"=>"https://journals.sagepub.com/doi/10.1177/13694332221119883", "uri"=>"", "uri_type"=>"", "citation"=>"Levine N.M., Narazaki Y., Spencer B.F., Jr. Performance-based post-earthquake building evaluations using computer vision-derived damage observations. Advances in Structural Engineering. 2022. doi:10.1177/13694332221119883", "dataset_id"=>2398, "selected_type"=>"", "datacite_list"=>"", "note"=>nil, "feature"=>nil} | 2025-01-08T23:48:49Z |
| RelatedMaterial | destroy: {"material_type"=>"Article", "availability"=>nil, "link"=>"", "uri"=>"", "uri_type"=>"", "citation"=>"Levine, N.M., Narazaki, Y., Spencer, B.F., Jr. \"Development of a Building Information Model-Guided Post-Earthquake Building Inspection Framework using 3D Synthetic Environments.\" Earthquake Engineering and Engineering Vibration, in press. ", "dataset_id"=>2398, "selected_type"=>"Article", "datacite_list"=>"", "note"=>nil, "feature"=>nil} | 2025-01-08T23:48:49Z |
| RelatedMaterial | destroy: {"material_type"=>"Thesis", "availability"=>nil, "link"=>"", "uri"=>"", "uri_type"=>"", "citation"=>"Levine, N.M. A Digital Twin Framework for Rapid Performance-Based Post-Earthquake Assessment Using Computer Vision and Building Information Models. PhD Dissertation, University of Illinois at Urbana-Champaign. 2022. ", "dataset_id"=>2398, "selected_type"=>"Thesis", "datacite_list"=>"", "note"=>nil, "feature"=>nil} | 2025-01-08T23:48:48Z |
| RelatedMaterial | update: {"uri"=>[nil, ""], "uri_type"=>[nil, ""], "datacite_list"=>[nil, ""]} | 2022-11-03T15:24:19Z |
| RelatedMaterial | update: {"uri"=>[nil, ""], "uri_type"=>[nil, ""], "datacite_list"=>[nil, ""]} | 2022-11-03T15:24:19Z |
| RelatedMaterial | update: {"uri"=>[nil, ""], "uri_type"=>[nil, ""], "datacite_list"=>[nil, ""]} | 2022-11-03T15:24:19Z |
| Dataset | update: {"keywords"=>["computer vision; earthquake engineering; structural health monitoring; ", "computer vision; earthquake engineering; structural health monitoring; civil engineering; structural engineering; "]} | 2022-09-30T13:35:45Z |