Deep learning models for road damages detection

Myles Cullen; Muhammad Mahmood Ali

doi:10.1364/ISA.2022.ITh3D.2

Deep learning models for road damages detection

Myles Cullen
, Muhammad Mahmood Ali

Atlantic Technological University
Mathematical Modelling and Intelligent Systems for Health and Environment (MISHE)

Research output: Contribution to journal › Conference article › peer-review

Abstract

This paper presents deep-learning-based image analysis for the detection and classification of road damage, tested for sample images from Ireland. Experimental results showed suitable performance for two of the most prevalent classes of road damage.

Original language	English
Article number	ITh3D.2
Journal	Optics InfoBase Conference Papers
DOIs	https://doi.org/10.1364/ISA.2022.ITh3D.2
Publication status	Published - 2022
Externally published	Yes
Event	Imaging Systems and Applications, ISA 2022 - Vancouver, Canada Duration: 11 Jul 2022 → 15 Jul 2022

Keywords

deep learning
damage detection

Name of Affiliated ATU Research Unit

MISHE - Mathematical Modelling and Intelligent Systems for Health & Environment

Access to Document

10.1364/ISA.2022.ITh3D.2

Cite this

@article{cb978f8259b54c89b43c9f3fd1c2a06a,

title = "Deep learning models for road damages detection",

abstract = "This paper presents deep-learning-based image analysis for the detection and classification of road damage, tested for sample images from Ireland. Experimental results showed suitable performance for two of the most prevalent classes of road damage.",

keywords = "deep learning, damage detection",

author = "Myles Cullen and Ali, \{Muhammad Mahmood\}",

note = "Publisher Copyright: {\textcopyright} 2022 The Author(s); Imaging Systems and Applications, ISA 2022 ; Conference date: 11-07-2022 Through 15-07-2022",

year = "2022",

doi = "10.1364/ISA.2022.ITh3D.2",

language = "English",

journal = "Optics InfoBase Conference Papers",

issn = "2162-2701",

}

TY - JOUR

T1 - Deep learning models for road damages detection

AU - Cullen, Myles

AU - Ali, Muhammad Mahmood

PY - 2022

Y1 - 2022

N2 - This paper presents deep-learning-based image analysis for the detection and classification of road damage, tested for sample images from Ireland. Experimental results showed suitable performance for two of the most prevalent classes of road damage.

AB - This paper presents deep-learning-based image analysis for the detection and classification of road damage, tested for sample images from Ireland. Experimental results showed suitable performance for two of the most prevalent classes of road damage.

KW - deep learning

KW - damage detection

UR - https://www.scopus.com/pages/publications/85139561053

U2 - 10.1364/ISA.2022.ITh3D.2

DO - 10.1364/ISA.2022.ITh3D.2

M3 - Conference article

AN - SCOPUS:85139561053

SN - 2162-2701

JO - Optics InfoBase Conference Papers

JF - Optics InfoBase Conference Papers

M1 - ITh3D.2

T2 - Imaging Systems and Applications, ISA 2022

Y2 - 11 July 2022 through 15 July 2022

ER -

Deep learning models for road damages detection

Abstract

Keywords

Name of Affiliated ATU Research Unit

Access to Document

Other files and links

Fingerprint

Cite this