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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. Please SUBSCRIBE to the channel for more content on Machine Learning, Deep Learning, Data Science, and Artificial Intelligence. Hoping to build a community of AI geeks. You'll fit right in! INVESTING [1] Webull (You can get 3 free stocks setting up a webull account today): https://a.webull.com/8XVa1znjYxio6ESdff REFERENCES [1] Main paper: https://arxiv.org/pdf/1703.06870v3.pdf [2] Code: https://github.com/facebookresearch/D... [3] Convolution Neural networks: • Convolution Neural Networks - EXPLAINED [4] Semantic segmentation in deep learning: http://blog.qure.ai/notes/semantic-se... [5] Top papers: http://www.arxiv-sanity.com/top?timef... [6] Recurrent Instance Segmentation: http://www.robots.ox.ac.uk/~tvg/publi... [7] Mask R-CNN Presentation by the Author: • Mask R-CNN [8] Mark Jay's Video: • Mask RCNN with Keras and Tensorflow (... [9] COCO dataset: http://cocodataset.org/#home [10] Fully Convolutional Networks: https://people.eecs.berkeley.edu/~jon... [11] Faster R-CNN explained: / faster-r-cnn-explained [12] Notes/summary of Masked R-CNN: http://www.shortscience.org/paper?bib... Music at : https://www.bensound.com/royalty-free...