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Machine learning algorithms application to road defects classification

... proposed approach is implemented in Matlab for automatic detection and classification of defects based on digital images analysis combined with machine learning algorithms such as the random forest algorithm and boosting. Segmentation is implemented using graph-cuts method and Markov random fields. The efficiency of proposed approach is demonstrated on the real data set. © 2018 - IOS Press and the authors. All rights reserved. входит

Теги: a random forest algorithm , boosting algorithm , graph-cuts method , markov random fields , pavement condition , road defects , adaptive boosting , artificial intelligence , decision trees , defects , feature extraction , graphic methods , image segmentation , learnin
Раздел: ИСЭМ СО РАН


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