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Foreign object debris detection in lane images using deep learning methodology

Foreign object debris detection in lane images using deep learning methodology

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_0e24cead2abe4e0398ddaea291e26162

Foreign object debris detection in lane images using deep learning methodology

About this item

Full title

Foreign object debris detection in lane images using deep learning methodology

Publisher

United States: PeerJ. Ltd

Journal title

PeerJ. Computer science, 2025-01, Vol.11, p.e2570, Article e2570

Language

English

Formats

Publication information

Publisher

United States: PeerJ. Ltd

More information

Scope and Contents

Contents

Foreign object debris (FOD) is an unwanted substance that damages vehicular systems, most commonly the wheels of vehicles. In airport runways, these foreign objects can damage the wheels or internal systems of planes, potentially leading to flight crashes. Surveys indicate that FOD-related damage costs over $4 billion annually, affecting airlines,...

Alternative Titles

Full title

Foreign object debris detection in lane images using deep learning methodology

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_doaj_primary_oai_doaj_org_article_0e24cead2abe4e0398ddaea291e26162

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_0e24cead2abe4e0398ddaea291e26162

Other Identifiers

ISSN

2376-5992

E-ISSN

2376-5992

DOI

10.7717/peerj-cs.2570

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