Reprint of “Two-stage sparse coding of region covariance via Log-Euclidean kernels to detect saliency”

Neural Networks

Volumn 92, Issue , 2017, Pages 47-59

  Zhang, Ying Ying ^a   Yang, Cai ^a   Zhang, Ping ^a  

^a NANYANG NORMAL UNIVERSITY   (China)

Author keywords

Log Euclidean kernel; Region covariance; Saliency; Sparse coding

Indexed keywords

COVARIANCE MATRIX; ERRORS; GEOMETRY; GRAPHIC METHODS; IMAGE CODING; PIXELS; SUPERPIXELS;

BOTTOM-UP SALIENCIES; LOG-EUCLIDEAN; POSTPROCESSING METHODS; REGION COVARIANCE; REGION COVARIANCE MATRIXES; SALIENCY; SPARSE CODING; STATE-OF-THE-ART METHODS;

CODES (SYMBOLS);

ACCURACY; ALGORITHM; ANALYTICAL ERROR; ARTICLE; COVARIANCE; EXPERIMENTAL STUDY; IMAGE QUALITY; IMAGE RECONSTRUCTION; KERNEL METHOD; MATHEMATICAL ANALYSIS; MATHEMATICAL COMPUTING; MATHEMATICAL PARAMETERS; PRIORITY JOURNAL; STATISTICAL MODEL; ARTIFICIAL NEURAL NETWORK; AUTOMATED PATTERN RECOGNITION; PROCEDURES;

ALGORITHMS; NEURAL NETWORKS (COMPUTER); PATTERN RECOGNITION, AUTOMATED;

EID: 85041257461     PISSN: 08936080     EISSN: 18792782     Source Type: Journal    
DOI: 10.1016/j.neunet.2017.06.001     Document Type: Article

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