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

Department of Mechatronic Engineering

Research output: Contribution to conference › Paper › 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
Pages	1-2
DOIs	https://doi.org/10.1364/ISA.2022.ITh3D.2
Publication status	Published - 2022
Event	Imaging and Applied Optics Congress 2022: Imaging Systems and Applications 2022 - Vancouver, British Columbia Canada, Vancouver, Canada Duration: 11 Jul 2022 → 15 Jul 2022 https://opg.optica.org/conference.cfm?meetingid=126&yr=2022

Conference

Conference	Imaging and Applied Optics Congress 2022
Country/Territory	Canada
City	Vancouver
Period	11/07/22 → 15/07/22
Internet address	https://opg.optica.org/conference.cfm?meetingid=126&yr=2022

Access to Document

10.1364/ISA.2022.ITh3D.2

Cite this

@conference{232a43c8a3384d06b7fbc0239828f7b4,

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}",

year = "2022",

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

language = "English",

pages = "1--2",

note = "Imaging and Applied Optics Congress 2022 ; Conference date: 11-07-2022 Through 15-07-2022",

url = "https://opg.optica.org/conference.cfm?meetingid=126&yr=2022",

}

TY - CONF

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.

U2 - 10.1364/ISA.2022.ITh3D.2

DO - 10.1364/ISA.2022.ITh3D.2

M3 - Paper

SP - 1

EP - 2

T2 - Imaging and Applied Optics Congress 2022

Y2 - 11 July 2022 through 15 July 2022

ER -

Deep Learning Models for Road Damages Detection

Abstract

Conference

Access to Document

Fingerprint

Cite this