Optics and Precision Engineering, Volume. 28, Issue 6, 1395(2020)
Ship detection based on the multi-scale visual saliency model
[1] [1] LENG X G, JI K F, XING X W, et al.. Area ratio invariant feature group for ship detection in sar imagery [J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2018, 11, 2376-2388.
LENG X G, JI K F, XING X W, et al.. Area ratio invariant feature group for ship detection in sar imagery [J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2018, 11, 2376-2388.
[2] [2] ZHOU H T, ZHUANG Y, CHEN L, et al.. Signal and Information Processing, Networking and Computers [M]. Singapore: Springer, 2018.
ZHOU H T, ZHUANG Y, CHEN L, et al.. Signal and Information Processing, Networking and Computers [M]. Singapore: Springer, 2018.
[7] [7] LIU W C, MA L, CHEN H. Arbitrary-oriented ship detection framework in optical remote-sensing images[J]. IEEE Geoscience and Remote Sensing Letters, 2018, 15, 937- 941.
LIU W C, MA L, CHEN H. Arbitrary-oriented ship detection framework in optical remote-sensing images[J]. IEEE Geoscience and Remote Sensing Letters, 2018, 15, 937- 941.
[8] [8] WU F, ZHOU Z Q, WANG B, et al.. Inshore ship detection based on convolutional neural network in optical satellite images[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2018, 11, 4005-4015.
WU F, ZHOU Z Q, WANG B, et al.. Inshore ship detection based on convolutional neural network in optical satellite images[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2018, 11, 4005-4015.
[9] [9] CHENG G, ZHOU P C, HAN J W. Learning rotation-invariant convolutional neural networks for object detection in VHR optical remote sensing images[J]. IEEE Transactions on Geoscience and Remote Sensing, 2016, 54, 7405-7415.
CHENG G, ZHOU P C, HAN J W. Learning rotation-invariant convolutional neural networks for object detection in VHR optical remote sensing images[J]. IEEE Transactions on Geoscience and Remote Sensing, 2016, 54, 7405-7415.
[10] [10] HOU X D, ZHANG L. Saliency detection: a spectral residual approach [C]. IEEE Conference on Computer Vision and Pattern Recognition, Minneapolis, 2007:1-8.
HOU X D, ZHANG L. Saliency detection: a spectral residual approach [C]. IEEE Conference on Computer Vision and Pattern Recognition, Minneapolis, 2007:1-8.
[11] [11] WONG J A, HARTIGAN H A. Algorithm AS 136: A K-means clustering algorithm[J]. Journal of the Royal Statistical Society. Series C (Applied Statistics), 1979, 28 (1):100-108.
WONG J A, HARTIGAN H A. Algorithm AS 136: A K-means clustering algorithm[J]. Journal of the Royal Statistical Society. Series C (Applied Statistics), 1979, 28 (1):100-108.
[12] [12] TAKACS G, CHANDRASEKHAR V, TSAI S, et al.. Unied real-time tracking and recognition with rotation-invariant fast features[C]. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, San Francisco, 2010: 934-941.
TAKACS G, CHANDRASEKHAR V, TSAI S, et al.. Unied real-time tracking and recognition with rotation-invariant fast features[C]. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, San Francisco, 2010: 934-941.
[13] [13] OTSU, N. A threshold selection method from gray-level histograms [J]. IEEE Transactions on Systems Man & Cybernetics, 1979, 9, 62-66.
OTSU, N. A threshold selection method from gray-level histograms [J]. IEEE Transactions on Systems Man & Cybernetics, 1979, 9, 62-66.
[14] [14] DALAL N, TRIGGS B. Histograms of oriented gradients for human detection [C]. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, San Diego, 2005: 886-893.
DALAL N, TRIGGS B. Histograms of oriented gradients for human detection [C]. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, San Diego, 2005: 886-893.
[15] [15] WANG J, JIANG H , YUAN Z , et al.. Salient object detection: A discriminative regional feature integration approach[J]. International Journal of Computer Vision, 2017, 123(2):251-268.
WANG J, JIANG H , YUAN Z , et al.. Salient object detection: A discriminative regional feature integration approach[J]. International Journal of Computer Vision, 2017, 123(2):251-268.
[16] [16] ERDEM E, ERDEM A. Visual saliency estimation by nonlinearly integrating features using region covariances[J]. Journal of Vision, 2013, 13(4):1-20.
ERDEM E, ERDEM A. Visual saliency estimation by nonlinearly integrating features using region covariances[J]. Journal of Vision, 2013, 13(4):1-20.
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ZHAO Hao-guang, WANG Ping, DONG Chao, SHANG Yang. Ship detection based on the multi-scale visual saliency model[J]. Optics and Precision Engineering, 2020, 28(6): 1395
Received: Dec. 12, 2019
Accepted: --
Published Online: Jun. 4, 2020
The Author Email: Chao DONG (dongchao315@mails.ucas.ac.cn)