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Depth learning methods for bridges inspection using UAV

Par Conseil national de recherches du Canada

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Lienhttps://www.intechopen.com/online-first/1153165
AuteurRechercher : 1; Rechercher : 1
Affiliation
  1. Conseil national de recherches Canada. Technologies numériques
FormatTexte, Article
Sujetdepth; 3D reconstruction; deep learning; bridge inspection; UAV
Résumé
This paper is investigating learning methods using depth as a cue measurement that can be used for bridge inspection. We investigate learning methods based on mono, stereo, and multiview image input and discuss the constraints that allow some methods to perform better than others in various scenarios. We go over the state-of-the-art deep learning methods, including supervised and unsupervised methods. These methods will be compared and evaluated, based on constraints, performance, and accuracy, and how top methods should be selected for each scenario. The same database should be used for fair comparison between all methods ensuring that evaluations are unbiased, replicable, and meaningful.
Date de publication
Maison d’éditionIntechOpen
Licence
Dans
  • Drones: Various Applications [Working Title] (7 février 2024).
Langueanglais
Publications évaluées par des pairsOui
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Identificateur de l’enregistrementec75122a-e32a-45e5-9f3d-c3fc71395755
Enregistrement créé2023-09-08
Enregistrement modifié2024-07-26
Date de modification :