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Image Segmentation Using Deep Learning: A Survey

大自然在召唤 2023-11-30 阅读 31
  1. 论文标题:Image Segmentation Using Deep Learning:A Survey
  2. 作者:
  3. 发表日期:
  4. 阅读日期 :
  5. 研究背景:scene understanding,medical image analysis, robotic perception, video surveillance, augmented reality, and image compression
  6. 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.
  1. Fully convolutional networks
  2. Convolutional models with graphical models
  3. Encoder-decoder based models
  4. 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
  5. Generative models and adversarial training
  6. Convolutional models with active contour models
  7. Other models
    在这里插入图片描述
  1. 研究结果:
  2. 创新点:
  3. 数据:
  4. 结论:
  5. 挑战:
  6. 研究展望:
  7. 重要性:
  8. 写作方法:
  • 主要讲各个方法细节,之后再了解
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