• Laser & Optoelectronics Progress
  • Vol. 57, Issue 12, 121013 (2020)
Likai Li1, Chihua Lu1、2, and Bin Zou1、2、*
Author Affiliations
  • 1Hubei Key Laboratory of Advanced Technology for Automotive Components, Wuhan University of Technology, Wuhan, Hubei 430070, China
  • 2Hubei Collaborative Innovation Center for Automotive Components Technology, Wuhan, Hubei 430070, China
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    DOI: 10.3788/LOP57.121013 Cite this Article Set citation alerts
    Likai Li, Chihua Lu, Bin Zou. Research on Target Detection and Feasible Region Segmentation Based on Deep Learning[J]. Laser & Optoelectronics Progress, 2020, 57(12): 121013 Copy Citation Text show less
    References

    [1] Li S S. The research of multi-object detection in traffic scene based on deep learning[D]. Changsha: Hunan University(2017).

    [2] Zhao H, An W S. Image salient object detection combined with deep learning[J]. Laser & Optoelectronics Progress, 55, 121003(2018).

    [3] Xu L X, Chen X J, Ban Y et al. Method for intelligent detection of parking spaces based on deep learning[J]. Chinese Journal of Lasers, 46, 0404013(2019).

    [4] Zhang X F, Liu J, Shi Z S et al. Review of deep learning-based semantic segmentation[J]. Laser & Optoelectronics Progress, 56, 150003(2019).

    [5] Shelhamer E, Long J, Darrell T. Fully convolutional networks for semantic segmentation[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 39, 640-651(2017).

    [6] 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).

    [7] Chen L C, Papandreou G, Kokkinos I et al. DeepLab: semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected CRFs[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 40, 834-848(2018).

    [8] Liu W, Anguelov D, Erhan D et al. SSD: single shot MultiBox detector[M]. ∥Leibe B, Matas J, Sebe N, et al. Computer Vision-ECCV 2016. Lecture Notes in Computer Science, Cham: Springer, 9905, 21-37(2016).

    [9] Simonyan K, Zisserman A[2019-08-30]. Very deep convolutional networks for large-scale image recognition[2019-08-30].https:∥arxiv., org/abs/1409, 1556.

    [10] Ioffe S, Szegedy C[2019-08-28]. Batch normalization: accelerating deep network training by reducing internal covariate shift[2019-08-28].https:∥arxiv., org/abs/1502, 03167.

    [11] Krizhevsky A, Sutskever I, Hinton G E. ImageNet classification with deep convolutional neural networks[J]. Communications of the ACM, 60, 84-90(2017).

    [12] 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, June 27-30, 2016, Las Vegas, NV, USA. New York: IEEE, 770-778(2016).

    [13] Teichmann M, Weber M, Zollner M et al. MultiNet: real-time joint semantic reasoning for autonomous driving. [C]∥2018 IEEE Intelligent Vehicles Symposium, June 26-30, 2018, Changshu,Jiangsu, China. New York: IEEE, 1013-1020(2018).

    [14] Ren S Q, He K M, Girshick R et al. Faster R-CNN: towards real-time object detection with region proposal networks[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 39, 1137-1149(2017).

    [15] Krizhevsky A, Sutskever I, Hinton G E. ImageNet classification with deep convolutional neural networks. [C]∥Proceedings of the 25th International Conference on Neural Information Processing Systems-Volume 1, December 3-6, 2012, Red Hook, NY, US. New York: ACM, 1097-1105(2012).

    [16] Smith L N. Cyclical learning rates for training neural networks. [C]∥2017 IEEE Winter Conference on Applications of Computer Vision, March 24-31, 2017, Santa Rosa, CA, USA. New York: IEEE, 464-472(2017).

    [17] Kingma D P, Ba J[2019-09-01]. Adam: a method for stochastic optimization[2019-09-01] https:∥arxiv., org/abs/1412, 6980.

    Likai Li, Chihua Lu, Bin Zou. Research on Target Detection and Feasible Region Segmentation Based on Deep Learning[J]. Laser & Optoelectronics Progress, 2020, 57(12): 121013
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