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Bounding box methods
A short video describing bounding box methods in deep learning and their applications. Includes R-CNN and YOLO.
Bounding box methods are a method that can provide information not only on the class of objects within an image, but also their location.
As we describe in the video the output of bounding box methods is commonly both the class of the object detected, and the spatial coordinates of a box sourrounding that object. Common bounding box methods mentioned in the video include R-CNN and YOLO.
