Why we use Saliency Map
In General, we take an image as input and we use the whole image to predict the output. So if we have an image of a bird and we predict bird but not the whole input is actually important and not the whole input contributes equally to predict the output. So if we have a really big image where only a few pixels the class we want to predict so computing the whole input is not a good idea i.e why we use a saliency map to highlight the important regions of the image and processed only the highlighted parts. It will actually help to relieve the computational burden.
What is Saliency Map?
Saliency Map is an important concept of deep learning and Computer vision. While training images of birds how does CNN knows to focus on bird-related pixels and ignore the leaves and the other background things in the image? By using the concept of Saliency Map.
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