<?xml version="1.0" encoding="ISO-8859-1"?><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
<front>
<journal-meta>
<journal-id>2007-6835</journal-id>
<journal-title><![CDATA[Revista ALCONPAT]]></journal-title>
<abbrev-journal-title><![CDATA[Rev. ALCONPAT]]></abbrev-journal-title>
<issn>2007-6835</issn>
<publisher>
<publisher-name><![CDATA[Asociación Latinoamericana de Control de Calidad, Patología y Recuperación de la Construcción A.C.]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S2007-68352025000100007</article-id>
<article-id pub-id-type="doi">10.21041/ra.v15i1.781</article-id>
<title-group>
<article-title xml:lang="en"><![CDATA[Defect detection using YOLOv8 for determining the condition of asphalt pavements]]></article-title>
<article-title xml:lang="es"><![CDATA[Detección de defectos con YOLOv8 para determinar el estado de los pavimentos asfálticos]]></article-title>
<article-title xml:lang="pt"><![CDATA[Detecção de defeitos utilizando YOLOv8 para determinação da condição de pavimentos asfálticos]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Souza]]></surname>
<given-names><![CDATA[A. M.]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Oliveira]]></surname>
<given-names><![CDATA[C. E.]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Decker]]></surname>
<given-names><![CDATA[P. H. B.]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Correa]]></surname>
<given-names><![CDATA[A. L. S. C.]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Amorim]]></surname>
<given-names><![CDATA[G. E. R.]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Fontenele]]></surname>
<given-names><![CDATA[H. B.]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,State University of Londrina Department of Civil Construction ]]></institution>
<addr-line><![CDATA[Londrina ]]></addr-line>
<country>Brazil</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>04</month>
<year>2025</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>04</month>
<year>2025</year>
</pub-date>
<volume>15</volume>
<numero>1</numero>
<fpage>79</fpage>
<lpage>91</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_arttext&amp;pid=S2007-68352025000100007&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_abstract&amp;pid=S2007-68352025000100007&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_pdf&amp;pid=S2007-68352025000100007&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="en"><p><![CDATA[ABSTRACT: This study aimed to evaluate the capacity of the YOLOv8 algorithm to detect potholes, patches, and cracks. To achieve this, a section of a highway was recorded, manually evaluated in the field, and compared with a semi-automatic evaluation based on video processing by the model. The model yielded different results from those obtained through field assessment. Although only a portion of the Maintenance Condition Index is used in the assessment, this marks the first use of an index integrated with YOLOv8. Thus, it is concluded that the model requires further improvements to become viable for definitive application.]]></p></abstract>
<abstract abstract-type="short" xml:lang="es"><p><![CDATA[RESUMEN: Este estudio tuvo como objetivo evaluar la capacidad de detectar baches, reparaciones y fisuras, utilizando el algoritmo YOLOv8. Para ello se filmó un tramo de una carretera, el cual fue evaluado en campo, de forma manual y comparado con una evaluación semiautomática basada en el procesamiento del video por parte del modelo. El uso del modelo produce varios resultados diferentes a los obtenidos mediante la evaluación de campo. Aunque en la evaluación solo se utiliza una parte del índice de condiciones de mantenimiento, es la primera vez que se utiliza un índice junto con YOLOv8. Por lo tanto, se concluye que el modelo requiere mejoras para ser viable y aplicarse definitivamente.]]></p></abstract>
<abstract abstract-type="short" xml:lang="pt"><p><![CDATA[RESUMO: Este trabalho objetivou avaliar a capacidade de detecção de buracos, remendos e trincas, por meio do algoritmo YOLOv8. Para isso, realizou-se uma filmagem do trecho de uma rodovia, que foi avaliada em campo, de forma manual e comparada com uma avaliação semiautomática a partir do processamento do vídeo pelo modelo. A utilização do modelo produz vários resultados diferentes dos obtidos por meio da avaliação em campo. Apesar de ser empregado apenas uma parcela do Índice de Condição de Manutenção na avaliação, é a primeira vez que um índice é utilizado em conjunto com o YOLOv8. Dessa forma, conclui-se que o modelo requer melhorias para se tornar viável e ser aplicado em definitivo.]]></p></abstract>
<kwd-group>
<kwd lng="en"><![CDATA[automation]]></kwd>
<kwd lng="en"><![CDATA[algorithm]]></kwd>
<kwd lng="en"><![CDATA[image]]></kwd>
<kwd lng="en"><![CDATA[computer vision]]></kwd>
<kwd lng="en"><![CDATA[object detection]]></kwd>
<kwd lng="es"><![CDATA[automatización]]></kwd>
<kwd lng="es"><![CDATA[algoritmo]]></kwd>
<kwd lng="es"><![CDATA[imagen]]></kwd>
<kwd lng="es"><![CDATA[visíon artificial]]></kwd>
<kwd lng="es"><![CDATA[detección de objetos]]></kwd>
<kwd lng="pt"><![CDATA[automação]]></kwd>
<kwd lng="pt"><![CDATA[algoritmo]]></kwd>
<kwd lng="pt"><![CDATA[imagem]]></kwd>
<kwd lng="pt"><![CDATA[visão computacional]]></kwd>
<kwd lng="pt"><![CDATA[detecção de objetos]]></kwd>
</kwd-group>
</article-meta>
</front><back>
<ref-list>
<ref id="B1">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Chunlong]]></surname>
<given-names><![CDATA[Z.]]></given-names>
</name>
<name>
<surname><![CDATA[Peile]]></surname>
<given-names><![CDATA[H.]]></given-names>
</name>
<name>
<surname><![CDATA[Shenghuai]]></surname>
<given-names><![CDATA[W.]]></given-names>
</name>
<name>
<surname><![CDATA[Chen]]></surname>
<given-names><![CDATA[W.]]></given-names>
</name>
<name>
<surname><![CDATA[Hongxia]]></surname>
<given-names><![CDATA[W.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Pavement Defect Detection Algorithm Based on Improved YOLOv7 Complex Background]]></article-title>
<source><![CDATA[IEEE Access]]></source>
<year>2024</year>
<volume>12</volume>
<page-range>32870-80</page-range></nlm-citation>
</ref>
<ref id="B2">
<nlm-citation citation-type="">
<collab>Confederação Nacional dos Transportes</collab>
<source><![CDATA[Pesquisa CNT de Rodovias 2023]]></source>
<year>2023</year>
</nlm-citation>
</ref>
<ref id="B3">
<nlm-citation citation-type="">
<collab>Departamento Nacional de Infraestrutura de Transportes</collab>
<source><![CDATA[Condições do Pavimento em março/2024]]></source>
<year>2024</year>
</nlm-citation>
</ref>
<ref id="B4">
<nlm-citation citation-type="">
<collab>Departamento Nacional de Infraestrutura de Transportes</collab>
<source><![CDATA[Resolução nº 5/2022, de 27 de abril de 2022]]></source>
<year>2024</year>
</nlm-citation>
</ref>
<ref id="B5">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Du]]></surname>
<given-names><![CDATA[F. J.]]></given-names>
</name>
<name>
<surname><![CDATA[Jiao]]></surname>
<given-names><![CDATA[S. J.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Improvement of Lightweight Convolutional Neural Network Model Based on YOLO Algorithm and Its Research in Pavement Defect Detection]]></article-title>
<source><![CDATA[Sensors]]></source>
<year>2022</year>
<volume>22</volume>
<numero>9</numero>
<issue>9</issue>
</nlm-citation>
</ref>
<ref id="B6">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Ju]]></surname>
<given-names><![CDATA[R. Y.]]></given-names>
</name>
<name>
<surname><![CDATA[Cai]]></surname>
<given-names><![CDATA[W.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Fracture detection in pediatric wrist trauma X-ray images using YOLOv8 algorithm]]></article-title>
<source><![CDATA[Scientific Reports]]></source>
<year>2023</year>
<volume>13</volume>
<numero>1</numero>
<issue>1</issue>
</nlm-citation>
</ref>
<ref id="B7">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[El Hakea]]></surname>
<given-names><![CDATA[A. H.]]></given-names>
</name>
<name>
<surname><![CDATA[Fakhr]]></surname>
<given-names><![CDATA[M. W.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Recent computer vision applications for pavement distress and condition assessment]]></article-title>
<source><![CDATA[Automation in Construction]]></source>
<year>2023</year>
<volume>146</volume>
<publisher-name><![CDATA[Elsevier B.V.]]></publisher-name>
</nlm-citation>
</ref>
<ref id="B8">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Gonçalves]]></surname>
<given-names><![CDATA[M.]]></given-names>
</name>
<name>
<surname><![CDATA[Marques]]></surname>
<given-names><![CDATA[T.]]></given-names>
</name>
<name>
<surname><![CDATA[Gaspar]]></surname>
<given-names><![CDATA[P. D.]]></given-names>
</name>
<name>
<surname><![CDATA[Soares]]></surname>
<given-names><![CDATA[V. N. G. J.]]></given-names>
</name>
<name>
<surname><![CDATA[Caldeira]]></surname>
<given-names><![CDATA[J. M. L. P.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Road Pavement Damage Detection using Computer Vision Techniques: Approaches, Challenges and Opportunities]]></article-title>
<source><![CDATA[Revista de Informatica Teorica e Aplicada]]></source>
<year>2023</year>
<volume>30</volume>
<numero>2</numero>
<issue>2</issue>
<page-range>22-35</page-range></nlm-citation>
</ref>
<ref id="B9">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Gong]]></surname>
<given-names><![CDATA[H.]]></given-names>
</name>
<name>
<surname><![CDATA[Te&#353;i&#263;]]></surname>
<given-names><![CDATA[J.]]></given-names>
</name>
<name>
<surname><![CDATA[Tao]]></surname>
<given-names><![CDATA[J.]]></given-names>
</name>
<name>
<surname><![CDATA[Luo]]></surname>
<given-names><![CDATA[X.]]></given-names>
</name>
<name>
<surname><![CDATA[Wang]]></surname>
<given-names><![CDATA[F.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Automated Pavement Crack Detection with Deep Learning Methods: What Are the Main Factors and How to Improve the Performance?]]></article-title>
<source><![CDATA[Transportation Research Record]]></source>
<year>2023</year>
<volume>2677</volume>
<numero>10</numero>
<issue>10</issue>
<page-range>311-23</page-range><publisher-name><![CDATA[SAGE Publications Ltd.]]></publisher-name>
</nlm-citation>
</ref>
<ref id="B10">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Huang]]></surname>
<given-names><![CDATA[P.]]></given-names>
</name>
<name>
<surname><![CDATA[Wang]]></surname>
<given-names><![CDATA[S.]]></given-names>
</name>
<name>
<surname><![CDATA[Chen]]></surname>
<given-names><![CDATA[J.]]></given-names>
</name>
<name>
<surname><![CDATA[Li]]></surname>
<given-names><![CDATA[W.]]></given-names>
</name>
<name>
<surname><![CDATA[Peng]]></surname>
<given-names><![CDATA[X.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Lightweight Model for Pavement Defect Detection Based on Improved YOLOv7]]></article-title>
<source><![CDATA[Sensors]]></source>
<year>2023</year>
<volume>23</volume>
<numero>16</numero>
<issue>16</issue>
</nlm-citation>
</ref>
<ref id="B11">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Hussain]]></surname>
<given-names><![CDATA[M.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[YOLO-v1 to YOLO-v8, the Rise of YOLO and Its Complementary Nature toward Digital Manufacturing and Industrial Defect Detection]]></article-title>
<source><![CDATA[Machines]]></source>
<year>2023</year>
<volume>11</volume>
<numero>7</numero>
<issue>7</issue>
<publisher-name><![CDATA[Multidisciplinary Digital Publishing Institute (MDPI)]]></publisher-name>
</nlm-citation>
</ref>
<ref id="B12">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Lin]]></surname>
<given-names><![CDATA[Y. C.]]></given-names>
</name>
<name>
<surname><![CDATA[Chen]]></surname>
<given-names><![CDATA[W. H.]]></given-names>
</name>
<name>
<surname><![CDATA[Kuo]]></surname>
<given-names><![CDATA[C. H.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Implementation of pavement defect detection system on edge computing platform]]></article-title>
<source><![CDATA[Applied Sciences]]></source>
<year>2021</year>
<volume>11</volume>
<numero>8</numero>
<issue>8</issue>
<publisher-loc><![CDATA[Switzerland ]]></publisher-loc>
</nlm-citation>
</ref>
<ref id="B13">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Lu]]></surname>
<given-names><![CDATA[J.]]></given-names>
</name>
<name>
<surname><![CDATA[Behbood]]></surname>
<given-names><![CDATA[V.]]></given-names>
</name>
<name>
<surname><![CDATA[Hao]]></surname>
<given-names><![CDATA[P.]]></given-names>
</name>
<name>
<surname><![CDATA[Zuo]]></surname>
<given-names><![CDATA[H.]]></given-names>
</name>
<name>
<surname><![CDATA[Xue]]></surname>
<given-names><![CDATA[S.]]></given-names>
</name>
<name>
<surname><![CDATA[Zhang]]></surname>
<given-names><![CDATA[G.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Transfer learning using computational intelligence: A survey]]></article-title>
<source><![CDATA[Knowledge-Based Systems]]></source>
<year>2015</year>
<volume>80</volume>
<page-range>14-23</page-range></nlm-citation>
</ref>
<ref id="B14">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Ma]]></surname>
<given-names><![CDATA[D.]]></given-names>
</name>
<name>
<surname><![CDATA[Fang]]></surname>
<given-names><![CDATA[H.]]></given-names>
</name>
<name>
<surname><![CDATA[Wang]]></surname>
<given-names><![CDATA[N.]]></given-names>
</name>
<name>
<surname><![CDATA[Zhang]]></surname>
<given-names><![CDATA[C.]]></given-names>
</name>
<name>
<surname><![CDATA[Dong]]></surname>
<given-names><![CDATA[J.]]></given-names>
</name>
<name>
<surname><![CDATA[Hu]]></surname>
<given-names><![CDATA[H.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Automatic Detection and Counting System for Pavement Cracks Based on PCGAN and YOLO-MF]]></article-title>
<source><![CDATA[IEEE Transactions on Intelligent Transportation Systems]]></source>
<year>2022</year>
<volume>23</volume>
<numero>11</numero>
<issue>11</issue>
<page-range>22166-78</page-range></nlm-citation>
</ref>
<ref id="B15">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Pan]]></surname>
<given-names><![CDATA[Y.]]></given-names>
</name>
<name>
<surname><![CDATA[Zhang]]></surname>
<given-names><![CDATA[L.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Roles of artificial intelligence in construction engineering and management: A critical review and future trends]]></article-title>
<source><![CDATA[Automation in Construction]]></source>
<year>2021</year>
<volume>122</volume>
<publisher-name><![CDATA[Elsevier B.V.]]></publisher-name>
</nlm-citation>
</ref>
<ref id="B16">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Terven]]></surname>
<given-names><![CDATA[J.]]></given-names>
</name>
<name>
<surname><![CDATA[Córdova-Esparza]]></surname>
<given-names><![CDATA[D. M.]]></given-names>
</name>
<name>
<surname><![CDATA[Romero-González]]></surname>
<given-names><![CDATA[J. A.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[A Comprehensive Review of YOLO Architectures in Computer Vision: From YOLOv1 to YOLOv8 and YOLO-NAS]]></article-title>
<source><![CDATA[Machine Learning and Knowledge Extraction]]></source>
<year>2023</year>
<volume>5</volume>
<numero>4</numero>
<issue>4</issue>
<page-range>1680-716</page-range><publisher-name><![CDATA[Multidisciplinary Digital Publishing Institute (MDPI)]]></publisher-name>
</nlm-citation>
</ref>
<ref id="B17">
<nlm-citation citation-type="">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Wang]]></surname>
<given-names><![CDATA[A.]]></given-names>
</name>
<name>
<surname><![CDATA[Chen]]></surname>
<given-names><![CDATA[H.]]></given-names>
</name>
<name>
<surname><![CDATA[Liu]]></surname>
<given-names><![CDATA[L.]]></given-names>
</name>
<name>
<surname><![CDATA[Chen]]></surname>
<given-names><![CDATA[K.]]></given-names>
</name>
<name>
<surname><![CDATA[Lin]]></surname>
<given-names><![CDATA[Z.]]></given-names>
</name>
<name>
<surname><![CDATA[Han]]></surname>
<given-names><![CDATA[J.]]></given-names>
</name>
<name>
<surname><![CDATA[Ding]]></surname>
<given-names><![CDATA[G.]]></given-names>
</name>
</person-group>
<source><![CDATA[YOLOv10: Real-Time End-to-End Object Detection]]></source>
<year>2024</year>
</nlm-citation>
</ref>
<ref id="B18">
<nlm-citation citation-type="">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Wang]]></surname>
<given-names><![CDATA[C.-Y.]]></given-names>
</name>
<name>
<surname><![CDATA[Yeh]]></surname>
<given-names><![CDATA[I.-H.]]></given-names>
</name>
<name>
<surname><![CDATA[Liao]]></surname>
<given-names><![CDATA[H.-Y. M.]]></given-names>
</name>
</person-group>
<source><![CDATA[YOLOv9: Learning What You Want to Learn Using Programmable Gradient Information]]></source>
<year>2024</year>
</nlm-citation>
</ref>
<ref id="B19">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Yao]]></surname>
<given-names><![CDATA[H.]]></given-names>
</name>
<name>
<surname><![CDATA[Fan]]></surname>
<given-names><![CDATA[Y.]]></given-names>
</name>
<name>
<surname><![CDATA[Wei]]></surname>
<given-names><![CDATA[X.]]></given-names>
</name>
<name>
<surname><![CDATA[Liu]]></surname>
<given-names><![CDATA[Y.]]></given-names>
</name>
<name>
<surname><![CDATA[Cao]]></surname>
<given-names><![CDATA[D.]]></given-names>
</name>
<name>
<surname><![CDATA[You]]></surname>
<given-names><![CDATA[Z.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Research and optimization of YOLO-based method for automatic pavement defect detection]]></article-title>
<source><![CDATA[Electronic Research Archive]]></source>
<year>2024</year>
<volume>32</volume>
<numero>3</numero>
<issue>3</issue>
<page-range>1708-30</page-range></nlm-citation>
</ref>
<ref id="B20">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Zhao]]></surname>
<given-names><![CDATA[Z. Q.]]></given-names>
</name>
<name>
<surname><![CDATA[Zheng]]></surname>
<given-names><![CDATA[P.]]></given-names>
</name>
<name>
<surname><![CDATA[Xu]]></surname>
<given-names><![CDATA[S. T.]]></given-names>
</name>
<name>
<surname><![CDATA[Wu]]></surname>
<given-names><![CDATA[X.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Object Detection with Deep Learning: A Review]]></article-title>
<source><![CDATA[IEEE Transactions on Neural Networks and Learning Systems]]></source>
<year>2019</year>
<volume>30</volume>
<numero>11</numero>
<issue>11</issue>
<page-range>3212-32</page-range><publisher-name><![CDATA[Institute of Electrical and Electronics Engineers Inc.]]></publisher-name>
</nlm-citation>
</ref>
</ref-list>
</back>
</article>
