[1] |
LONG J,SHELHAMER E,DARRELL T.Fully convolutional networks for semantic segmentation[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition.Washington D.C.,USA:IEEE Press,2015:3431-3440.
|
[2] |
KRIZHEVSKY A,SUTSKEVER I,HINTON G E.Imagenet classification with deep convolutional neural networks[C]//Proceedings of Advances in Neural Information Processing Systems.Red Hook,USA:Curran Associates,Inc.,2012:1097-1105.
|
[3] |
SIMONYAN K,ZISSERMAN A.Very deep convolutional networks for large-scale image recognition[EB/OL].[2019-03-01].https://arxiv.xilesou.top/abs/1409.1556.
|
[4] |
SZEGEDY C,LIU W,JIA Y,et al.Going deeper with convolutions[C]//Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.Washington D.C.,USA:IEEE Press,2015:1-9.
|
[5] |
HU Jie,SHEN Li,SUN Gang.Squeeze-and-excitation networks[C]//Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.Washington D.C.,USA:IEEE Press,2018:7132-7141.
|
[6] |
KENDALL A,BADRINARAYANAN V,CIPOLLA R.Bayesian segnet:model uncertainty in deep convolutional encoder-decoder architectures for scene understanding[EB/OL].[2019-03-01].https://arxiv.xilesou.top/abs/1511.02680.
|
[7] |
RONNEBERGER O,FISCHER P,BROX T.U-net:convolutional networks for biomedical image segmentation[C]//Proceedings of International Conference on Medical Image Computing and Computer-Assisted Intervention.Berlin,Germany:Springer,2015:234-241.
|
[8] |
YU F,KOLTUN V.Multi-scale context aggregation by dilated convolutions[EB/OL].[2019-03-01].https://arxiv.xilesou.top/abs/1511.07122.
|
[9] |
LIN G,MILAN A,SHEN C,et al.Refinenet:multi-path refinement networks for high-resolution semantic segmentation[C]//Proceedings of IEEE Conferenceon Computer Vision and Pattern Recognition.Washington D.C.,USA:IEEE Press,2017:1925-1934.
|
[10] |
LU Wenchao,PANG Yanwei,HE Yuqing,et al.Real-time and accurate semantic segmentation based on separable residual modules[J].Laser and Optoelectronics Progress,2019,56(5):89-99.(in Chinese) 路文超,庞彦伟,何宇清,等.基于可分离残差模块的精确实时语义分割[J].激光与光电子学进展,2019,56(5):89-99.
|
[11] |
PENG Chao,Zhang Xiangyu,YU Gang,et al.Large kernel matters——improve semantic segmentation by global convolutional network[EB/OL].[2019-02-15].https://arxiv.org/abs/1703.02719
|
[12] |
HE Kaiming,ZHANG Xiangyu,REN Shaoqing,et al.Deep residual learning for image recognition[C]//Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.Washington D.C.,USA:IEEE Press,2016:770-778.
|
[13] |
CHEN L C,PAPANDREOU G,SCHROFF F,et al.Rethinking Atrous convolution for semantic image segmentation[EB/OL].[2019-03-01].https://arxiv.xilesou.top/abs/1706.05587.
|
[14] |
HUANG Tinghong,NIE Zhuozhen,WANG Qingguo,et al.Image real-time semantic segmentation based on block adaptive feature fusion[J/OL].Acta Automatica Sinica:1-12[2019-03-01].https://doi.org/10.16383/j.aas.c180645.(in Chinese) 黄庭鸿,聂卓赟,王庆国,等.基于区块自适应特征融合的图像实时语义分割[J/OL].自动化学报:1-12[2019-03-01].https://doi.org/10.16383/j.aas.c180645.
|
[15] |
WU Zhizhen,GAO Yongming,LI Lei,et al.A full convolutional network method for semantic segmentation of non-equilibrium remote sensing images[J].Acta Optica Sinica:2019,39(4):1-12.(in Chinese) 吴止锾,高永明,李磊,等.类别非均衡遥感图像语义分割的全卷积网络方法[J].光学学报,2019,39(4):1-12.
|
[16] |
CHEN L C,ZHU Y,PAPANDREOU G,et al.Encoder-decoder with Atrous separable convolution for semantic image segmentation[C]//Proceedings of European Conference on Computer Vision.Berlin,Germany:Springer,2018:801-818.
|
[17] |
PASZKE A,CHAURASIA A,KIM S,et al.Enet:a deep neural network architecture for real-time semantic segmentation[EB/OL].[2019-03-01].https://arxiv.xilesou.top/abs/1606.02147
|
[18] |
ZHANG Ting,QI Guojun,XIAO Bin,et al.Interleaved group convolutions[C]//Proceedings of IEEE International Conference on Computer Vision.Washington D.C.,USA:IEEE Press,2017:4373-4382.
|
[19] |
WANG R J,LI X,LING C X.Pelee:a real-time object detection system on mobile devices[C]//Proceedings of Advances in Neural Information Processing Systems.Red Hook,USA:Curran Associates,Inc.,2018:1963-1972.
|
[20] |
LI Wanyi,WANG Peng,QIAO Hong.A survey of target tracking methods introducing visual attention mechanism[J].Journal of Automation,2014,40(4):561-576.(in Chinese) 黎万义,王鹏,乔红.引入视觉注意机制的目标跟踪方法综述[J].自动化学报,2014,40(4):561-576.
|
[21] |
TAN Li,YANG Minghua,CAO Yuanda,et al.Image fusion based on dynamic attention in video sensor network[J].Computer Engineering,2010,36(2):214-216,219.(in Chinese) 谭励,杨明华,曹元大,等.视频传感器网络中基于动态注意力的图像融合[J].计算机工程,2010,36(2):214-216, 219.
|
[22] |
FENG Xingjie,ZHANG Le,ZENG Yunze.Problem similarity calculation based on multi-note CNN[J].Computer Engineering,2019,45(9):284-290.(in Chinese) 冯兴杰,张乐,曾云泽.基于多注意力CNN的问题相似度计算[J].计算机工程,2019,45(9):284-290.
|
[23] |
SHI Xingjian,CHEN Zhourong,WANG Hao,et al.Convolutional LSTM network:a machine learning approach for precipitation nowcasting[C]//Proceedings of Advances in Neural Information Processing Systems.Cambridge,USA:MIT Press,2015:802-810.
|
[24] |
HUANG G,LIU S,VAN DER MAATEN L,et al.Condensenet:an efficient DenseNet using learned group convolutions[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition.Washington D.C.,USA:IEEE Press,2018:2752-2761.
|
[25] |
CORDTS M,OMRAN M,RAMOS S,et al.The cityscapes dataset for semantic urban scene understanding[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition.Washington D.C.,USA:IEEE Press,2016:3213-3223.
|
[26] |
ZHOU B,ZHAO H,PUIG X,et al.Scene parsing through ADE20K dataset[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition.Washington D.C.,USA:IEEE Press,2017:633-641.
|
[27] |
RUDER S.An overview of gradient descent optimization algorithms[EB/OL].[2019-03-01].https://arxiv.xilesou.top/abs/1609.04747.
|
[28] |
BOSMAN P A N,THIERENS D.Adaptive variance scaling in continuous multi-objective estimation-of-distribution algorithms[C]//Proceedings of the 9th Annual Conference on Genetic and Evolutionary Computation.New York,USA:ACM Press,2007:500-507.
|