Hybrid Human-Artificial Intelligence Approach for Pavement Distress Assessment (PICUCHA)

Thumbnail image of item number 1 in: 'Hybrid Human-Artificial Intelligence Approach for Pavement Distress Assessment (PICUCHA)'.
Thumbnail image of item number 2 in: 'Hybrid Human-Artificial Intelligence Approach for Pavement Distress Assessment (PICUCHA)'.
Thumbnail image of item number 3 in: 'Hybrid Human-Artificial Intelligence Approach for Pavement Distress Assessment (PICUCHA)'.
Thumbnail image of item number 4 in: 'Hybrid Human-Artificial Intelligence Approach for Pavement Distress Assessment (PICUCHA)'.
Showing 1-4 of 12 pages in this article.

PDF Version Also Available for Download.

Description

This article proposes a new method named PICture Unsupervised Classification with Human Analysis (PICUCHA) to circumvent many of the limitations of existing approaches, based on a combination of human and artificial intelligence.

Physical Description

12 p.

Creation Information

Salini, Reus; Xu, Bugao & Carvalho, Regis July 2017.

Context

This article is part of the collection entitled: UNT Scholarly Works and was provided by the UNT College of Merchandising, Hospitality and Tourism to the UNT Digital Library, a digital repository hosted by the UNT Libraries. It has been viewed 350 times. More information about this article can be viewed below.

Who

People and organizations associated with either the creation of this article or its content.

Authors

Publisher

Provided By

UNT College of Merchandising, Hospitality and Tourism

The UNT College of Merchandising, Hospitality, and Tourism educates students for the globalization of the hospitality, retail, and tourism industries. The college provides bachelor's and master's programs in a variety of majors.

About | Browse this Partner

Contact Us

Corrections Questions

What

Descriptive information to help identify this article. Follow the links below to find similar items on the Digital Library.

Description

This article proposes a new method named PICture Unsupervised Classification with Human Analysis (PICUCHA) to circumvent many of the limitations of existing approaches, based on a combination of human and artificial intelligence.

Physical Description

12 p.

Notes

Abstract: The pavement surface condition assessment is a critical component for a proper pavement management system as well as for pavement rehabilitation design. A number of devices were developed to automatically record surface distresses in a continuous survey mode, but the software required for automatic distress identification remains a big challenge. In this study, a new method named PICture Unsupervised Classification with Human Analysis (PICUCHA) is proposed to circumvent many of the limitations of existing approaches, based on a combination of human and artificial intelligence. It was designed from scratch to be capable to identify sealed and unsealed cracks, potholes, patches, different types of pavements and others. The self-learning algorithms do not use any distresses predefinition and can process images taken by cameras with different brands, technologies and resolution. This study describes some key aspects of the new method and provides examples in which PICUCHA was tested in real conditions showing accuracy up to 96.9% in image pattern detection and classification.

Source

  • Stavebni Obzor - Civil Engineering Journal, 2017. Prague, Czech Republic: Czech Technical University.

Language

Item Type

Identifier

Unique identifying numbers for this article in the Digital Library or other systems.

Publication Information

  • Publication Title: Stavebni Obzor - Civil Engineering Journal
  • Pages: 12
  • Page Start: 143
  • Page End: 154
  • Peer Reviewed: Yes

Collections

This article is part of the following collection of related materials.

UNT Scholarly Works

Materials from the UNT community's research, creative, and scholarly activities and UNT's Open Access Repository. Access to some items in this collection may be restricted.

About | Browse this Collection

What responsibilities do I have when using this article?

Digital Files

When

Dates and time periods associated with this article.

Creation Date

  • July 2017

Added to The UNT Digital Library

  • Aug. 29, 2017, 9:38 a.m.

Description Last Updated

  • Dec. 7, 2020, 12:59 p.m.

Usage Statistics

When was this article last used?

Yesterday: 0
Past 30 days: 0
Total Uses: 350
More Statistics

Interact With This Article

Here are some suggestions for what to do next.

Start Reading

Thumbnail image of item number 1 in: 'Hybrid Human-Artificial Intelligence Approach for Pavement Distress Assessment (PICUCHA)'.
Thumbnail image of item number 2 in: 'Hybrid Human-Artificial Intelligence Approach for Pavement Distress Assessment (PICUCHA)'.
Thumbnail image of item number 3 in: 'Hybrid Human-Artificial Intelligence Approach for Pavement Distress Assessment (PICUCHA)'.
Thumbnail image of item number 4 in: 'Hybrid Human-Artificial Intelligence Approach for Pavement Distress Assessment (PICUCHA)'.

PDF Version Also Available for Download.

Citations, Rights, Re-Use

International Image Interoperability Framework

IIF Logo

We support the IIIF Presentation API

Links for Robots

Helpful links in machine-readable formats.

Archival Resource Key (ARK)

International Image Interoperability Framework (IIIF)

Metadata Formats

Images

URLs

Stats

Salini, Reus; Xu, Bugao & Carvalho, Regis. Hybrid Human-Artificial Intelligence Approach for Pavement Distress Assessment (PICUCHA), article, July 2017; Prague, Czech Republic. (https://digital.library.unt.edu/ark:/67531/metadc990977/: accessed April 27, 2024), University of North Texas Libraries, UNT Digital Library, https://digital.library.unt.edu; crediting UNT College of Merchandising, Hospitality and Tourism.

Back to Top of Screen