Machine learning algorithms application to road defects classification

Intelligent Decision Technologies

Volumn 12, Issue 1, 2018, Pages 59-66

  Nguyen, T H ^a   Nguyen, T L ^a   Sidorov, D N ^a,c   Dreglea, A I ^b  

^a IRKUTSK NATIONAL RESEARCH TECHNICAL UNIVERSITY   (Russian Federation)

^b VINOGRADOV INSTITUTE OF GEOCHEMISTRY   (Russian Federation)

^c ENERGY SYSTEMS INSTITUTE   (Russian Federation)

Author keywords

a random forest algorithm; boosting algorithm; graph cuts method; Markov random fields; pavement condition; Road defects

Indexed keywords

ADAPTIVE BOOSTING; ARTIFICIAL INTELLIGENCE; DECISION TREES; DEFECTS; FEATURE EXTRACTION; GRAPHIC METHODS; IMAGE SEGMENTATION; LEARNING SYSTEMS; MARKOV PROCESSES; ROADS AND STREETS;

BOOSTING ALGORITHM; GRAPH CUT; MARKOV RANDOM FIELDS; PAVEMENT CONDITION; RANDOM FOREST ALGORITHM;

LEARNING ALGORITHMS;

EID: 85044348039     PISSN: 18724981     EISSN: 18758843     Source Type: Journal    
DOI: 10.3233/IDT-170323     Document Type: Conference Paper

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