Gradient-weighted Class Activation Mapping
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May 1, 2024
4 minute read
Gradient-weighted Class Activation Mapping (Grad-CAM) is a technique used to visualize the important regions of an image that contribute to the prediction of a deep learning model. It is a useful tool for understanding how deep learning models make decisions and for identifying potential biases or errors in the model.
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There are several reasons why you might want to learn about Gradient-weighted Class Activation Mapping:
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Find a path to becoming a Gradient-weighted Class Activation Mapping. Learn more at:
OpenCourser.com/topic/onutwy/gradient
