Home > Archive>Volume 13, Issue 2, 2017 >151-155. DOI:10.1007/s11801-017-7014-9
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Ship detection in optical remote sensing image based on visual saliency and AdaBoost classifier
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1. Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China;2. University of Chinese Academy of Sciences, Beijing 100039, China

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    Abstract:

    efficiency switch and modulation.

    Reference
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    [7]Z. Song, H. Sui and Y. Wang, Automatic Ship Detection for Optical Satellite Images Based on Visual Attention Model and LBP, IEEE Workshop on Electronics, Computer and Applications, Ottawa, 722 (2014).
    [8]F. Yang, Q. Xu, F. Gao and L. Hu, Ship Detection from Optical Satellite Images Based on Visual Search Mechanism, IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Milan, 3679 (2015).
    [9]S. Qi, J. Ma, J. Lin, Y. Li and J. Tian, IEEE Geoscience and Remote Sensing Letters 12, 1451 (2015).
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    [12]R. Achanta, A. Shaji, K. Smith, A. Lucchi, P. Fua and S. Süsstrunk, Slic Superpixels, EPFL Technical Report, 149300 (2010).
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WANG Hui-li, ZHU Ming, LIN Chun-bo, CHEN Dian-bing. Ship detection in optical remote sensing image based on visual saliency and AdaBoost classifier[J]. Optoelectronics Letters,2017,13(2):151-155

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History
  • Received:January 17,2017
  • Revised:February 10,2017
  • Online: November 02,2017
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