- 论文标题：Image Segmentation Using Deep Learning:A Survey
- 作者：
- 发表日期：
- 阅读日期 ：
- 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
- Generative models and adversarial training
- Convolutional models with active contour models
- Other models
原文地址:https://blog.csdn.net/qq_61735602/article/details/134687310
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