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Volumn , Issue , 2010, Pages 3757-3760

K-nearest neighbor search: Fast GPU-based implementations and application to high-dimensional feature matching

Author keywords

CUDA CUBLAS; GPU; k nearest neighbors; SIFT

Indexed keywords

GRAPHICS PROCESSING UNIT; LEARNING ALGORITHMS; MEMBERSHIP FUNCTIONS; MOTION COMPENSATION; TEXT PROCESSING;

EID: 78651079861     PISSN: 15224880     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICIP.2010.5654017     Document Type: Conference Paper
Times cited : (165)

References (10)
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  • 3
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    • (2004) J. Biomed. Inform. , vol.37 , pp. 240-248
    • Pan, F.1    Wang, B.2    Hu, X.3    Perrizo, W.4
  • 4
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    • An optimal algorithm for approximate nearest neighbor searching fixed dimensions
    • S. Arya, D. M. Mount, N. S. Netanyahu, R. Silverman, and A. Y. Wu, "An optimal algorithm for approximate nearest neighbor searching fixed dimensions," Journal of the ACM, vol. 45, pp. 891-923, 1998.
    • (1998) Journal of the ACM , vol.45 , pp. 891-923
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  • 5
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    • Searching with quantization: Approximate nearest neighbor search using short codes and distance estimators
    • H. Jégou, M. Douze, and C. Schmid, "Searching with quantization: approximate nearest neighbor search using short codes and distance estimators," Tech. Rep. RR-7020, INRIA, 2009.
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    • Jégou, H.1    Douze, M.2    Schmid, C.3
  • 9
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    • Distinctive image features from scale-invariant keypoints
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    • Lowe, D.G.1
  • 10
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    • Hamming embedding and weak geometric consistency for large scale image search
    • Marseille, France
    • H. Jégou, M. Douze, and C. Schmid, "Hamming embedding and weak geometric consistency for large scale image search," in European Conference on Computer Vision, Marseille, France, 2008.
    • (2008) European Conference on Computer Vision
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.