Structure Inspector Computer Vision Project
This COCO-Bridge_readme.txt file was generated on [2019-04-28] by [Eric Bianchi]
GENERAL INFORMATION
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Title of Dataset: ***COCO-Bridge, structural details for bridge inspection
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The author, a Virginia Tech graduate and PhD student, ERIC BIANCHI in the SEM (structural engineering and materials) program in the college of civil engineering.
Principal Investigator Contact Information
Name: Matthew Hebdon
Institution: Virginia Tech, SEM, college of civil engineering
Address: 105B Patton Hall, 750 Drillfield Dr. Blacksburg, VA 24061
Email: mhebdon@vt.edu
Associate or Co-investigator Contact Information
Name: Pretap Tokekar
Institution: Virginia Tech, ECE, college of electrical and computer engineering
Address: 453 Whittemore, Virginia Tech, Blacskburg, VA 24061
Email: tokekar@vt.edu
Alternate Contact Information
Name: Eric Bianchi
Institution: Virginia Tech
Address: 185 Sequoia Cir, Christiansburg VA, 24073
Email: beric7@vt.edu
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Date of data collection: ***from (2018-08) to (2019-03)
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Geographic location of data collection (where was data collected?): ***Norfolk Southern Railway yard in Roanoke Virginia and from engineering firms (Clark Nexsen, VDOT)
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Information about funding sources that supported the collection of the data: ***National Science Foundation (NSF)
SHARING/ACCESS INFORMATION
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Licenses/restrictions placed on the data: ***Cite the Dataset as outlined in #6 (Recommended citation for the data)
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Links to publications that cite or use the data: ***(Currently, no other publications use this data)
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Links to other publicly accessible locations of the data: ***(http://COCO-bridge.com, https://github.com/beric7/COCO-Bridge)
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Links/relationships to ancillary data sets: ***There are no ancillary data sets included at the moment
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Was data derived from another source?
If yes, list source(s): ***NO. -
Recommended citation for the data: ***(Bianchi, E. (2018).COCO-Bridge [Dataset]. University Libraries, Virginia Tech.)
Trained Model API
This project has a trained model available that you can try in your browser and use to get predictions via our Hosted Inference API and other deployment methods.