HomeOwner SearchCategory Search
A Universal Convolution Neural Network (U-CNN) for Highly Accurate Defect Detection in Civil Infrastructure Inspection
Visit USCO
hero image
Computer File Registration
Copyright Title

A Universal Convolution Neural Network (U-CNN) for Highly Accurate Defect Detection in Civil Infrastructure Inspection

Status

Published

on 23 Jul 2019
Year of Creation
2018
Copyright Claimant
University of Nevada Reno
Registration Number
TX0008779913
on 23 Jul 2019

Copyright Summary


The U.S. Copyright record (Registration Number: TX0008779913) dated 23 Jul 2019, pertains to an electronic file (eService) titled "A Universal Convolution Neural Network (U-CNN) for Highly Accurate Defect Detection in Civil Infrastructure Inspection" created in 2018. The copyright holder is University of Nevada Reno, known for their creative contributions in computer file registration. For any inquiries concerning this copyrighted material, kindly reach out to University of Nevada Reno.

Copyright Details


Copyright Claimant
University of Nevada Reno

Application Details


Registration Number
TX0008779913
Registration Date
7/23/2019
Year of Creation
2018
Agency Marc Code
DLC-CO
Record Status
Changed
Corporate Author
University of Nevada Reno
Physical Description
Electronic file (eService)
First Publication Nation
Brazil

Corporate Authors


Notes


Rights Note: Shannon Sheehan, University of Nevada Reno, 1664 N. Virginia St MS 0321, Reno, NV, 89512, United States, (775) 784-7721, ssheehan@unr.edu

Statements


Application Title Statement: A Universal Convolution Neural Network (U-CNN) for Highly Accurate Defect Detection in Civil Infrastructure Inspection
Author Statement: University of Nevada Reno employer for hire Citizenship: United States Authorship: computer program
Get your copyright registered todayThousands have copyrighted their assets.
What are you waiting for?

© 2024 reserved by Trademarkia
Show terms & conditions