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Advanced Convolutional Neural Networks
The second definition leads to the intuition behind the Mask R-CNN network. The
Mask R-CNN is a Faster R-CNN with an additional CNN in front of its regression
head, which takes as input the bounding box coordinates reported for each ROI
and converts it to a binary mask [11]:
Figure 8: Mask R-CNN architecture
In April 2019, Google released Mask R-CNN in open source, pretrained with TPUs
(https://colab.research.google.com/github/tensorflow/tpu/blob/master/
models/official/mask_rcnn/mask_rcnn_demo.ipynb). I suggest playing with the
Colab notebook to see what the results are. In Figure 9 we see an example of image
segmentation:
Figure 9: An example of image segmentation
Google also released another model trained on TPUs called DeepLab and you can
see an image (Figure 10) from the demo (https://colab.research.google.com/
github/tensorflow/models/blob/master/research/deeplab/deeplab_demo.
ipynb#scrollTo=edGukUHXyymr):
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