Acta Optica Sinica, Volume. 40, Issue 1, 0111018(2020)

Infrared-Remote-Sensing Ship Detection Based on Lightweight Residual Network

Tianyou Zhu1,2,3, Lingfeng Huang1,2,3, Feng Dong1,2, and Huixing Gong1,2、*
Author Affiliations
  • 1Key Laboratory of Infrared System Detection and Imaging Technology, Chinese Academy of Sciences, Shanghai 200083, China
  • 2Shanghai Institute of Technical Physics, Chinese Academy of Sciences, Shanghai 200083, China
  • 3University of Chinese Academy of Sciences, Beijing 100049, China
  • show less
    References(16)

    [3] Jiang B T, Ma X F, Lu Y et al. Ship detection in spaceborne infrared images based on convolutional neural networks and synthetic targets[J]. Infrared Physics & Technology, 97, 229-234(2019).

    [5] Li Q P, Mou L C, Liu Q J et al. HSF-Net: multiscale deep feature embedding for ship detection in optical remote sensing imagery[J]. IEEE Transactions on Geoscience and Remote Sensing, 56, 7147-7161(2018).

    [6] 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, 54, 7405-7415(2016).

    [7] Ronneberger O, Fischer P, Brox T. U-Net: convolutional networks for biomedical image segmentation[M]. //Navab N, Hornegger J, Wells W, et al. Medical image computing and computer-assisted intervention-MICCAI 2015. Lecture notes in computer science. Cham: Springer, 9351, 234-241(2015).

    [8] Badrinarayanan V, Kendall A, Cipolla R. SegNet: a deep convolutional encoder-decoder architecture for image segmentation[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 39, 2481-2495(2017).

    [9] Courbariaux M, Bengio Y, David J P. BinaryConnect: training deep neural networks with binary weights during propagations. [C]//Proceedings of the 28th International Conference on Neural Information Processing Systems, December 7-12, 2015, Montreal, Canada. Canada: NIPS, 3123-3131(2015).

    [10] Hubara I, Courbariaux M, Soudry D et al. Binarized neural networks. [C]//Advances in Neural Information Processing Systems 29 (NIPS 2016), December 5-10, 2016, Barcelona, Spain. Canada: NIPS, 4107-4115(2016).

    [12] Zhang X Y, Zhou X Y, Lin M X et al. ShuffleNet: an extremely efficient convolutional neural network for mobile devices. [C]//2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, June 18-23, 2018, Salt Lake City, UT, USA. New York: IEEE, 6848-6856(2018).

    [14] Romera E, Alvarez J M, Bergasa L M et al. ERFNet: efficient residual factorized ConvNet for real-time semantic segmentation[J]. IEEE Transactions on Intelligent Transportation Systems, 19, 263-272(2018).

    [15] Glorot X, Bordes A, Bengio Y. Deep sparse rectifier neural networks[C]//Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics, April 11-13, 2011, Fort Lauderdale, USA., 315-323(2011).

    [16] He K M, Zhang X Y, Ren S Q et al. Deep residual learning for image recognition. [C]//2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 27-30, 2016, Las Vegas, NV, USA. New York: IEEE, 770-778(2016).

    Tools

    Get Citation

    Copy Citation Text

    Tianyou Zhu, Lingfeng Huang, Feng Dong, Huixing Gong. Infrared-Remote-Sensing Ship Detection Based on Lightweight Residual Network[J]. Acta Optica Sinica, 2020, 40(1): 0111018

    Download Citation

    EndNote(RIS)BibTexPlain Text
    Save article for my favorites
    Paper Information

    Category: Special Issue on Computational Optical Imaging

    Received: Jul. 26, 2019

    Accepted: Sep. 9, 2019

    Published Online: Jan. 6, 2020

    The Author Email: Gong Huixing (hxgong@mail.sitp.ac.cn)

    DOI:10.3788/AOS202040.0111018

    Topics