CNN Heat Maps: Gradients vs. DeconvNets vs. Guided Backpropagation

Rachel Draelos, MD, PhD
Towards Data Science
9 min readOct 6, 2019

--

This post summarizes three closely related methods for creating saliency maps: Gradients (2013), DeconvNets (2014), and Guided Backpropagation (2014). Saliency maps are heat maps that are intended to provide insight into what aspects of an input image a convolutional neural network is using to make a prediction. All three of the methods discussed in this post are a form of

--

--

CEO at Cydoc | Physician Scientist | MD + Computer Science PhD | AI/ML Innovator