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This project extends support for DeepLabV3+ implementation on TensorFlow with multiple backbones, including: ResNet50/101/V2, DenseNet121/169, MobileNet/V2, and VGG16/19.

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Neurojedi/DeepLabV3Plus-TF-Backbones

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DeepLabV3Plus-TF-Backbones

This repository extends the Keras example code for Multiclass semantic segmentation using DeepLabV3+. While the original example utilized a ResNet50 backbone, my work focuses on adapting the network to support various backbones available in tensorflow.keras.applications.

Currently, the model can be used with the following backbones:

  1. ResNet50
  2. ResNet101
  3. ResNet50V2
  4. ResNet101V2
  5. DenseNet121
  6. DenseNet169
  7. MobileNet
  8. MobileNetV2
  9. VGG16
  10. VGG19

In my experiments, I found the following backbones were ineffective:

  1. ConvNeXtSmall
  2. ConvNeXtTiny
  3. ConvNeXtBase
  4. ConvNeXtLarge
  5. EfficientNetB0
  6. EfficientNetB1
  7. EfficientNetB2
  8. EfficientNetB3
  9. EfficientNetB4
  10. EfficientNetB5
  11. EfficientNetB6
  12. EfficientNetB7
  13. EfficientNetV2B0
  14. EfficientNetV2B1
  15. EfficientNetV2B2
  16. EfficientNetV2B3
  17. NASNetLarge

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This project extends support for DeepLabV3+ implementation on TensorFlow with multiple backbones, including: ResNet50/101/V2, DenseNet121/169, MobileNet/V2, and VGG16/19.

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