메뉴 건너뛰기




Volumn 10, Issue 11, 2014, Pages 1385-1393

Visual sewer inspection: detail of coding system versus data quality?

Author keywords

accuracy; assessment; errors; inspection; sewers and drains

Indexed keywords

DEFECTS; ERRORS; INSPECTION; SEWERS;

EID: 84907288910     PISSN: 15732479     EISSN: 17448980     Source Type: Journal    
DOI: 10.1080/15732479.2013.816974     Document Type: Article
Times cited : (22)

References (11)
  • 5
    • 67349235961 scopus 로고    scopus 로고
    • Automated defect detection for sewer pipeline inspection and condition assessment
    • Guo, W., Soibelman, L., & Garrett, J.H.Jr. (2009). Automated defect detection for sewer pipeline inspection and condition assessment. Automation in Construction, 18, 587–596.
    • (2009) Automation in Construction , vol.18 , pp. 587-596
    • Guo, W.1    Soibelman, L.2    Garrett, J.H.3
  • 8
    • 39749093168 scopus 로고
    • The magical number seven, plus or minus two: some limits on our capacity for information processing
    • Miller, G.A. (1956). The magical number seven, plus or minus two: some limits on our capacity for information processing. Psychological Review, 63(2), 81–97.
    • (1956) Psychological Review , vol.63 , Issue.2 , pp. 81-97
    • Miller, G.A.1
  • 11
    • 44949223479 scopus 로고    scopus 로고
    • Automated diagnosis of sewer pipe defects based on machine learning approaches
    • Yang, M.-D., & Su, T.-C. (2008). Automated diagnosis of sewer pipe defects based on machine learning approaches. Expert Systems with Applications, 35, 1327–1337.
    • (2008) Expert Systems with Applications , vol.35 , pp. 1327-1337
    • Yang, M.-D.1    Su, T.-C.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.