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deeplabv3plus (Google's new algorithm for semantic segmentation) in keras:Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation

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Deeplab v3+ in keras

DeepLab is a state-of-art deep learning model for semantic image segmentation. For tensorflow implemention, please refer to [tensorflow/models/research]: https://github.com/tensorflow/models/tree/master/research/deeplab

The Features of DeepLab v3+

  • Encoder-Decoder Structures
  • Atrous Convolutions in ASPP structure
  • Separable Convolutions instead of traditional Convolutions
  • Bilinear Interpolation instead of Transpose Convolutions

The Brief Structure

Encoder

  1. Xception as the Feature Extractor
  2. ASPP
  3. Separable Convolutions

Decoder

  1. Upsampling
  2. Separable Convolutions

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deeplabv3plus (Google's new algorithm for semantic segmentation) in keras:Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation

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