{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,23]],"date-time":"2026-01-23T23:31:01Z","timestamp":1769211061756,"version":"3.49.0"},"reference-count":31,"publisher":"MDPI AG","issue":"21","license":[{"start":{"date-parts":[[2019,11,3]],"date-time":"2019-11-03T00:00:00Z","timestamp":1572739200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100004663","name":"Ministry of Science and Technology, Taiwan","doi-asserted-by":"publisher","award":["MOST 108-2221-E-035-069 -"],"award-info":[{"award-number":["MOST 108-2221-E-035-069 -"]}],"id":[{"id":"10.13039\/501100004663","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>In this study, an innovative, ensemble learning method in a dynamic imaging system of an unmanned vehicle is presented. The feasibility of the system was tested in the crack detection of a retaining wall in a climbing area or a mountain road. The unmanned vehicle can provide a lightweight and remote cruise routine with a Geographic Information System sensor, a Gyro sensor, and a charge-coupled device camera. The crack was the target to be tested, and the retaining wall was patrolled through the drone flight path setting, and then the horizontal image was instantly returned by using the wireless transmission of the system. That is based on the cascade classifier, and the feature comparison classifier was designed further, and then the machine vision correlation algorithm was used to analyze the target type information. First, the system collects the target image and background to establish the samples database, and then uses the Local Binary Patterns feature extraction algorithm to extract the feature values for classification. When the first stage classification is completed, the classification results are target features, and edge feature comparisons. The innovative ensemble learning classifier was used to analyze the image and determine the location of the crack for risk assessment.<\/jats:p>","DOI":"10.3390\/s19214784","type":"journal-article","created":{"date-parts":[[2019,11,4]],"date-time":"2019-11-04T04:13:08Z","timestamp":1572840788000},"page":"4784","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["Crack Detection on a Retaining Wall with an Innovative, Ensemble Learning Method in a Dynamic Imaging System"],"prefix":"10.3390","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5299-9624","authenticated-orcid":false,"given":"Chern-Sheng","family":"Lin","sequence":"first","affiliation":[{"name":"Department of Automatic Control Engineering, Feng Chia University, Taichung 407, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shih-Hua","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Automatic Control Engineering, Feng Chia University, Taichung 407, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Che-Ming","family":"Chang","sequence":"additional","affiliation":[{"name":"Ph.D. Program of Electrical and Communications Engineering, Feng Chia University, Taichung 407, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tsu-Wang","family":"Shen","sequence":"additional","affiliation":[{"name":"Department of Automatic Control Engineering, Feng Chia University, Taichung 407, Taiwan"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2019,11,3]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"194","DOI":"10.1016\/j.measurement.2018.01.039","article-title":"The Remote Cruise Method for the Robot with Multiple Sensors","volume":"118","author":"Lin","year":"2018","journal-title":"Measurement"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"787","DOI":"10.1016\/S0305-0548(02)00051-5","article-title":"A Genetic Algorithm for the Vehicle Routing Problem","volume":"30","author":"Baker","year":"2003","journal-title":"Comput. 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