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Volumn 2016-November, Issue , 2016, Pages 755-758

Application of ReliefF algorithm to selecting feature sets for classification of high resolution remote sensing image

Author keywords

classification; feature selection; ReliefF algorithm

Indexed keywords


EID: 85007495769     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IGARSS.2016.7729190     Document Type: Conference Paper
Times cited : (54)

References (6)
  • 2
    • 70349332954 scopus 로고    scopus 로고
    • A novel approach to the selection of spatially invariant features for the classification of hyperspectral images with improved generalization capability
    • L. Bruzzone and C. Persello, "A novel approach to the selection of spatially invariant features for the classification of hyperspectral images with improved generalization capability, " IEEE Transactions on Geoscience and Remote Sensing, vol. 47, pp. 3180-3191, 2009.
    • (2009) IEEE Transactions on Geoscience and Remote Sensing , vol.47 , pp. 3180-3191
    • Bruzzone, L.1    Persello, C.2
  • 3
  • 5
    • 84921832467 scopus 로고    scopus 로고
    • Evaluating ReliefF-based multi-label feature selection algorithm
    • N. Spolar and M. C. Monard, "Evaluating ReliefF-based multi-label feature selection algorithm, " Lecture Notes in Computer Science, vol. 8864, pp. 194-205, 2014.
    • (2014) Lecture Notes in Computer Science , vol.8864 , pp. 194-205
    • Spolar, N.1    Monard, M.C.2
  • 6
    • 85007436967 scopus 로고    scopus 로고
    • Multiple features remote sensing image classification based on combining ReliefF and mRMR
    • L. Wang, "Multiple features remote sensing image classification based on combining ReliefF and mRMR, " Chinese Journal of Stereology and Image Analysis, vol. 19, pp. 250-256, 2014.
    • (2014) Chinese Journal of Stereology and Image Analysis , vol.19 , pp. 250-256
    • Wang, L.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.