메뉴 건너뛰기




Volumn 13, Issue 2, 2002, Pages 393-401

Classification of underground pipe scanned images using feature extraction and neuro-fuzzy algorithm

Author keywords

Backpropagation algorithm; Crack features; Image processing; Neural networks; Neuro fuzzy algorithms; Pipe defect classification; Pipeline inspection

Indexed keywords

ALGORITHMS; ARTIFICIAL INTELLIGENCE; BACKPROPAGATION; CRACKS; FUZZY SETS; IMAGE ANALYSIS; LEARNING SYSTEMS; MEMBERSHIP FUNCTIONS; NEURAL NETWORKS; PIPELINES; SCANNING;

EID: 0036505126     PISSN: 10459227     EISSN: None     Source Type: Journal    
DOI: 10.1109/72.991425     Document Type: Article
Times cited : (47)

References (53)
  • 26
    • 0029696432 scopus 로고    scopus 로고
    • Neural network based cloud detection/classification using textural and spectral features
    • Lincoln, NB
    • (1996) Proc. IGRASS , pp. 1105-1107
    • Shaikh, M.A.1    Tian, B.2
  • 27
    • 0028603789 scopus 로고
    • Cloud classification of AVHRR imagery in maritime using a probabilistic neural network
    • (1994) J. Appl. Meterol. , vol.33 , pp. 909-918
    • Bankert, R.L.1
  • 28
    • 0001352883 scopus 로고
    • A neural network based methodology for pavement crack detection and classification
    • Washington, DC: Transportation Res. Board
    • (1993) Transp. Res. , vol.1 , pp. 275-291
    • Kaseko, M.S.1    Ritchie, S.G.2
  • 38
    • 0002300771 scopus 로고
    • Some potential applications of artificial neural systems in financial management
    • April
    • (1993) J. Syst. Mgmt. , pp. 12-15
    • Hsieh, C.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.