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Volumn 2016-November, Issue , 2016, Pages 5091-5094

How useful is region-based classification of remote sensing images in a deep learning framework?

Author keywords

Deep learning; Image classification; Remote sensing; Segmentation algorithms; Superpixels

Indexed keywords


EID: 85007500060     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IGARSS.2016.7730327     Document Type: Conference Paper
Times cited : (36)

References (12)
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    • Lagrange, A.1
  • 5
    • 85007431891 scopus 로고    scopus 로고
    • Superpixel-based unsupervised change detection using multi-dimensional change vector analysis and SVM-based classification
    • July
    • Z. Wu et al., "Superpixel-Based Unsupervised Change Detection Using Multi-Dimensional Change Vector Analysis and Svm-Based Classification," ISPRS Ann. Photogramm. Remote Sens. Spat. Inf. Sci, vol. 7, pp. 257-262, July 2012
    • (2012) ISPRS Ann. Photogramm. Remote Sens. Spat. Inf. Sci , vol.7 , pp. 257-262
    • Wu, Z.1
  • 6
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  • 10
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    • Best merge region-growing segmentation with integrated non-adjacent region object aggregation
    • Nov
    • J. Tilton et al., "Best Merge Region-Growing Segmentation With Integrated Non-adjacent Region Object Aggregation," Trans. on Geosci. And Remote Sens., vol. 50, no. 11, pp. 4454-4467, Nov. 2012
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  • 11
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    • Rottensteiner, F.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.