Semantic Damage Segmentation for Aircraft Engine Borescope Videos-Reference-Cited by-同舟云学术

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Semantic Damage Segmentation for Aircraft Engine Borescope Videos

Published:2022-08 Issue:8 Volume:19 Page:565-573
ISSN:2327-3097
Container-title:Journal of Aerospace Information Systems
language:en
Short-container-title:Journal of Aerospace Information Systems

Author:

Xiao Renrui¹^ORCID,Wan Xili¹,Li Yifeng¹,Guan Xinjie¹^ORCID,Huang Xu¹

Affiliation:

1. Nanjing Tech University, 211800 Nanjing, People’s Republic of China

Funder

National Natural Science Foundation of China

Postgraduate Research Practice Innovation Program of Jiangsu Province

Publisher

American Institute of Aeronautics and Astronautics (AIAA)

Subject

Electrical and Electronic Engineering,Computer Science Applications,Aerospace Engineering

Link

https://arc.aiaa.org/doi/pdf/10.2514/1.I011051

Reference24 articles.

1. DruryC. G.WatsonJ. “Human Factors Good Practices in Borescope Inspection,” Vol. 8, Federal Aviation Administration/Office of Aviation Medicine, Washington, D.C. 2002.

2. Using Convolutional Neural Networks to Automate Aircraft Maintenance Visual Inspection

3. Underground sewer pipe condition assessment based on convolutional neural networks

4. Automatic pixel‐level multiple damage detection of concrete structure using fully convolutional network

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