Mask Region based Convolution Neural Networks - EXPLAINED!
Channel: CodeEmporium
Date: 2018-02-26

In this video, we will take a look at new type of neural network architecture called "Masked Region based Convolution Neural Networks", Masked R-CNN for short. And in the process, highlight some key sub problems in computer vision.

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REFERENCES

[1] Main paper: https://arxiv.org/pdf/1703.06870v3.pdf
[2] Code: https://github.com/facebookresearch/Detectron
[3] Convolution Neural networks: https://www.youtube.com/watch?v=m8pOnJxOcqY
[4] Semantic segmentation in deep learning: http://blog.qure.ai/notes/semantic-segmentation-deep-learning-review
[5] Top papers: http://www.arxiv-sanity.com/top?timefilter=alltime&vfilter=all
[6] Recurrent Instance Segmentation: http://www.robots.ox.ac.uk/~tvg/publications/2016/RIS7.pdf
[7] Mask R-CNN Presentation by the Author: https://www.youtube.com/watch?v=g7z4mkfRjI4
[8] Mark Jay's Video: https://www.youtube.com/watch?v=2TikTv6PWDw
[9] COCO dataset: http://cocodataset.org/#home
[10] Fully Convolutional Networks: https://people.eecs.berkeley.edu/~jonlong/long_shelhamer_fcn.pdf
[11] Faster R-CNN explained: https://medium.com/@smallfishbigsea/faster-r-cnn-explained-864d4fb7e3f8
[12] Notes/summary of Masked R-CNN: http://www.shortscience.org/paper?bibtexKey=journals/corr/HeGDG17#aleju

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