Deep Learning Models for Road Damages Detection

Myles Cullen; Muhammad Mahmood Ali

Deep Learning Models for Road Damages Detection

Department of Mechatronic Engineering

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
Publication status	Published - 2022
Event	Imaging Systems and Applications, ISA 2022 - Vancouver, Canada Duration: 11 Jul 2022 → 15 Jul 2022

Cite this

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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.",

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",

language = "English",

journal = "Optics InfoBase Conference Papers",

issn = "2162-2701",

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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.

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

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

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