References
- Xu Fang. Research on key Technologies for Automatic Detection of Surface Objects in Visible light remote sensing images [D]. University of Chinese Academy of Sciences (Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences), 2018.
- Zhang Zemiao, Huo Huan, Zhao Fengyu. Review of Object detection algorithms for deep convolutional neural networks [J]. Minicomputers, 2019, 40(09): 1825-1831.
- Yao Qunli, HU Xian, LEI Hong. Research Progress of Deep convolutional neural network in Object Detection [J]. Computer Engineering and Applications, 2016,54(17):1–9.
- Xu Junfeng, Zhang Baoming, Guo Haitao. A multi-feature fusion object-oriented multi-source remote sensing image change detection method [J]. Journal of surveying and mapping science and technology, 2015, 32(05):505–509.
- Sun Hao, Sun Xian, Wang Hongqi. Research on a high-resolution remote sensing image ship detection method [J]. Surveying and mapping science, 2013, 38(5):112–116.
- Wang Tengfei. Research on high-resolution Remote Sensing Image Deep Learning Ship Detection Technology [D]. Harbin Institute of Technology, 2017.
- Wang Jinchuan, TAN Xicheng, WANG Zhaohai, ZHONG Yanfei, Dong Huaping, Zhou Songtao, Cheng Boyi. Research on remote sensing image Object recognition Method based on Faster R-CNN Deep Network [J]. Journal of Earth Information Science, 2016, 20(10):1500–1508.
- Yao Hongge, Wang Cheng, Yu Jun, Bai Xiaojun, Li Wei. Small Object ship identification in complex satellite images [J]. Journal of remote sensing, 2020, 24(02): 116-125.
- Wu Jinliang, WANG Gang, Liang Shuo, Chen Jinyong, Gao Feng. Research on Ship Object Detection based on Mask R-CNN [J]. Radio Engineering, 2008, 48(11):947–952.
- He Yubo, LIU Kun. Surface Significance Object Detection based on convolutional neural network [J/OL]. Computer Engineering and Application:1–10[2020-06-09].
- Ren S Q, He K M, Girshick R, et al. Faster R-CNN: towards real-time object detection with region proposal networks [J]. Computer Science, 2015(99):1.
- Zhang Y, Sohn K, Villegas R, et al Improving object detection with deep convolutional networks via Bayesian optimization and structured prediction[C]. Computer Vision and Pattern Recognition. IEEE, 2015:249–258
- Girshick R. Fast R-CNN[C]. the IEEE International Conference on Computer Vision, December 7-13, 2015, Chile. New Jersey, IEEE Press, 2015:1440–1448.
- Engineering; Study Data from Northeast Electric Power University Provide New Insights into Engineering (Fingerprint location algorithm based on K-means for spatial farthest access point in Wi-Fi environment)[J]. Journal of Engineering, 2020.