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Crack Identification Based on Computer Vision

This special issue belongs to the section “Information Processes“.

Special Issue Information

Dear Colleagues,

With the construction and operation of traffic and geotechnical structures, the generation of cracks on the surfaces of structures and rock masses poses a significant threat to the safety of engineering. The accurate identification of cracks is essential in evaluation safety in a timely manner and enhancing the stability of engineering. Driven by the vigorous development of computer performance, computer vision technology takes the initiative in the realization of the above goals. Therefore, the aim of this Special Issue is to present the application of novel technology and concepts based on computer vision in crack identification.

The scope of this Special Issue includes, but is not limited to, the following topics: crack detection in civil structures, crack identification in surface or underground rock mass, crack detection in concrete structures, the identification of the location of material fatigue crack initiation, railway track visual inspection and crack detection, pavement crack detection and identification, bridge crack automatic detection, and crack identification in other transportation infrastructure surfaces. In addition, we welcome the submission of articles that present research on the combination of computer vision techniques and artificial intelligence models.

Dr. Chuanqi Li
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Information is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • computer vision
  • crack identification
  • artificial intelligence models

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Information - ISSN 2078-2489