论文标题：Image Segmentation Using Deep Learning:A Survey
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研究背景：scene understanding,medical image analysis, robotic perception, video surveillance, augmented reality, and image compression
方法和性质： fully convolutional pixel-labeling networks,encoder-decoder architectures, multi-scale and pyramid based approaches, recurrent networks, visual attention models, and generativemodels in adversarial settings.
Fully convolutional networks
Convolutional models with graphical models
Encoder-decoder based models
Multi-scale and pyramid network based models5) R-CNN based models (for instance segmentation)6) Dilated convolutional models and DeepLab family7) Recurrent neural network based models8) Attention-based models
