Multiscale deep fully convolutional network for sea-land segmentation of surveillance images
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[1] Enhua Wu,et al. Squeeze-and-Excitation Networks , 2017, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[2] Yoshua Bengio,et al. Deep Sparse Rectifier Neural Networks , 2011, AISTATS.
[3] Luca Antiga,et al. Automatic differentiation in PyTorch , 2017 .
[4] Thomas Brox,et al. U-Net: Convolutional Networks for Biomedical Image Segmentation , 2015, MICCAI.
[5] Zhenwei Shi,et al. Maritime Semantic Labeling of Optical Remote Sensing Images with Multi-Scale Fully Convolutional Network , 2017, Remote. Sens..
[6] Gaofeng Meng,et al. Efficient sea-land segmentation using seeds learning and edge directed graph cut , 2016, Neurocomputing.
[7] Hui Zhou,et al. A Novel Hierarchical Method of Ship Detection from Spaceborne Optical Image Based on Shape and Texture Features , 2010, IEEE Transactions on Geoscience and Remote Sensing.
[8] Jimmy Ba,et al. Adam: A Method for Stochastic Optimization , 2014, ICLR.
[9] H. Liu,et al. Automated extraction of coastline from satellite imagery by integrating Canny edge detection and locally adaptive thresholding methods , 2004 .
[10] Trevor Darrell,et al. Fully Convolutional Networks for Semantic Segmentation , 2017, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[11] Linda G. Shapiro,et al. ESPNet: Efficient Spatial Pyramid of Dilated Convolutions for Semantic Segmentation , 2018, ECCV.
[12] George Papandreou,et al. Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation , 2018, ECCV.
[13] Lihua Yue,et al. A Novel Sea-Land Segmentation Algorithm Based on Local Binary Patterns for Ship Detection , 2014 .
[14] Seunghoon Hong,et al. Learning Deconvolution Network for Semantic Segmentation , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).