激光与光电子学进展, 2020, 57 (14): 141004, 网络出版: 2020-07-24  

用于多光谱语义分割的LBP特征增强神经网络 下载: 550次

A Neural Network for Multi-Spectral Semantic Segmentation Based on LBP Feature Enhancement
作者单位
1 天津大学微电子学院, 天津 300072
2 天津市成像与感知微电子技术重点实验室, 天津 300072
引用该论文

史兴萍, 徐江涛, 蒋永唐, 秦书臻, 路凯歌. 用于多光谱语义分割的LBP特征增强神经网络[J]. 激光与光电子学进展, 2020, 57(14): 141004.

Xingping Shi, Jiangtao Xu, Yongtang Jiang, Shuzhen Qin, Kaige Lu. A Neural Network for Multi-Spectral Semantic Segmentation Based on LBP Feature Enhancement[J]. Laser & Optoelectronics Progress, 2020, 57(14): 141004.

参考文献

[1] 郭继舜. 面向自动驾驶的语义分割和目标检测技术[D]. 成都: 电子科技大学, 2018: 1- 5.

    Guo JS. Semantic image segmentation and object detection in autonomous-driving system[D]. Chengdu: University of Electronic Science and Technology of China, 2018: 1- 5.

[2] 黄星奕, 丘子明, 许燕. 基于深度监督全卷积神经网络的MRI脑图像语义分割算法[J]. 北京生物医学工程, 2019, 38(3): 277-282.

    Huang X Y, Qiu Z M, Xu Y. Semantic segmentation algorithm for MRI brain image based on deeply supervised fully convolutional network[J]. Beijing Biomedical Engineering, 2019, 38(3): 277-282.

[3] 刘丹, 马同伟. 结合语义信息的行人检测方法[J]. 电子测量与仪器学报, 2019, 33(1): 54-60.

    Liu D, Ma T W. Pedestrian detection method based on semantic information[J]. Journal of Electronic Measurement and Instrumentation, 2019, 33(1): 54-60.

[4] 伍鹏瑛. 基于卷积神经网络的真实场景下行人检测研究[D]. 长沙: 长沙理工大学, 2018: 5- 8.

    Wu PY. Research on pedestrian detection in real scene based on convolutional neural network[D]. Changsha: Changsha University of Science & Technology, 2018: 5- 8.

[5] 朱天佑, 董峰, 龚惠兴. 基于二值语义分割网络的遥感建筑物检测[J]. 光学学报, 2019, 39(12): 1228002.

    Zhu T Y, Dong F, Gong H X. Remote sensing building detection based on binarized semantic segmentation[J]. Acta Optica Sinica, 2019, 39(12): 1228002.

[6] 张祥甫, 刘健, 石章松, 等. 基于深度学习的语义分割问题研究综述[J]. 激光与光电子学进展, 2019, 56(15): 150003.

    Zhang X F, Liu J, Shi Z S, et al. Review of deep learning-based semantic segmentation[J]. Laser & Optoelectronics Progress, 2019, 56(15): 150003.

[7] 王嫣然, 陈清亮, 吴俊君. 面向复杂环境的图像语义分割方法综述[J]. 计算机科学, 2019, 46(9): 36-46.

    Wang Y R, Chen Q L, Wu J J. Research on image semantic segmentation for complex environments[J]. Computer Science, 2019, 46(9): 36-46.

[8] 王恩德, 齐凯, 李学鹏, 等. 基于神经网络的遥感图像语义分割方法[J]. 光学学报, 2019, 39(12): 1210001.

    Wang E D, Qi K, Li X P, et al. Semantic segmentation of remote sensing image based on neural network[J]. Acta Optica Sinica, 2019, 39(12): 1210001.

[9] Lin GS, MilanA, Shen CH, et al. RefineNet: multi-path refinement networks for high-resolution semantic segmentation[C]∥2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), July 21-26, 2017. Honolulu, HI. IEEE, 2017: 1925- 1934.

[10] 郭呈呈, 于凤芹, 陈莹. 基于卷积神经网络特征和改进超像素匹配的图像语义分割[J]. 激光与光电子学进展, 2018, 55(8): 081005.

    Guo C C, Yu F Q, Chen Y. Image semantic segmentation based on convolutional neural network feature and improved superpixel matching[J]. Laser & Optoelectronics Progress, 2018, 55(8): 081005.

[11] 程晓悦, 赵龙章, 胡穹, 等. 基于膨胀卷积平滑及轻型上采样的实时语义分割[J]. 激光与光电子学进展, 2020, 57(2): 021017.

    Cheng X Y, Zhao L Z, Hu Q, et al. Real-time semantic segmentation based on dilated convolution[J]. Laser & Optoelectronics Progress, 2020, 57(2): 021017.

[12] HazirbasC, Ma LN, DomokosC, et al.FuseNet: incorporating depth into semantic segmentation via fusion-based CNN architecture[M] ∥Computer Vision-ACCV 2016. Cham: Springer International Publishing, 2017: 213- 228.

[13] Ha QS, WatanabeK, KarasawaT, et al. MFNet: towards real-time semantic segmentation for autonomous vehicles with multi-spectral scenes[C]∥2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), September 24-28, 2017. Vancouver, BC. IEEE, 2017: 5108- 5115.

[14] Sun Y X, Zuo W X, Liu M. RTFNet: RGB-thermal fusion network for semantic segmentation of urban scenes[J]. IEEE Robotics and Automation Letters, 2019, 4(3): 2576-2583.

[15] Ojala T, Pietikäinen M, Harwood D. A comparative study of texture measures with classification based on featured distributions[J]. Pattern Recognition, 1996, 29(1): 51-59.

[16] He KM, Zhang XY, Ren SQ, 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. IEEE, 2016: 770- 778.

[17] 徐杰, 孙超, 郭春赫. 实时系统下LBP与CNN结合的人脸识别方法[J]. 黑龙江科技大学学报, 2018, 28(6): 692-696.

    Xu J, Sun C, Guo C H. Face recognition based on combination of LBP and CNN in real-time system[J]. Journal of Heilongjiang University of Science and Technology, 2018, 28(6): 692-696.

[18] DengJ, DongW, SocherR, et al. ImageNet: a large-scale hierarchical image database[C]∥2009 IEEE Conference on Computer Vision and Pattern Recognition, June 20-25, 2009. Miami, FL. IEEE, 2009: 248- 255.

史兴萍, 徐江涛, 蒋永唐, 秦书臻, 路凯歌. 用于多光谱语义分割的LBP特征增强神经网络[J]. 激光与光电子学进展, 2020, 57(14): 141004. Xingping Shi, Jiangtao Xu, Yongtang Jiang, Shuzhen Qin, Kaige Lu. A Neural Network for Multi-Spectral Semantic Segmentation Based on LBP Feature Enhancement[J]. Laser & Optoelectronics Progress, 2020, 57(14): 141004.

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