'''Region Based-based Convolutional Neural Networks (R-CNN)''' are a family of machine learning models for [[computer vision]] and specifically [[object detection]].
== History ==
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== Applications ==
Region-based Basedconvolutional Convolutionalneural Neural Networksnetworks have been used for tracking objects from a drone-mounted camera,<ref>{{Cite news|last=Nene|first=Vidi|url=https://dronebelow.com/2019/08/02/deep-learning-based-real-time-multiple-object-detection-and-tracking-via-drone/|title=Deep Learning-Based Real-Time Multiple-Object Detection and Tracking via Drone|date=Aug 2, 2019|work=Drone Below|access-date=Mar 28, 2020|url-status=live}}</ref> locating text in an image,<ref>{{Cite news|last=Ray|first=Tiernan|url=https://www.zdnet.com/article/facebook-pumps-up-character-recognition-to-mine-memes/|title=Facebook pumps up character recognition to mine memes|date=Sep 11, 2018|work=ZDnet|access-date=Mar 28, 2020|url-status=live}}</ref> and enabling object detection in [[Google Lens]].<ref>{{Cite news|last=Sagar|first=Ram|url=https://analyticsindiamag.com/these-machine-learning-techniques-make-google-lens-a-success/|title=These machine learning methods make google lens a success|date=Sep 9, 2019|work=Analytics India|access-date=Mar 28, 2020|url-status=live}}</ref> Mask R-CNN serves as one of seven tasks in the MLPerf Training Benchmark, which is a competition to speed up the training of neural networks.<ref>{{cite arXiv|eprint=1910.01500v3|class=math.LG|first=Peter|last=Mattson|title=MLPerf Training Benchmark|date=2019|display-authors=etal}}</ref>
