What are Feature Maps?
Feature maps enable us to capture the output activations of convolutional layers, providing insights into how the network processes and interprets input data at various stages.
- Feature maps are the outputs of particular filters or kernels that are applied to an input image using convolutional layers in a convolutional neural network (CNN).
- These feature maps assist in capturing the different facets or patterns present in the input image.
- Each feature map highlights specific features, such as edges, textures, or other higher-level features that the network has learned.
Visualizing Feature Maps using PyTorch
Interpreting and visualizing feature maps in PyTorch is like looking at snapshots of what’s happening inside a neural network as it processes information. In this Tutorial, we will walk through interpreting and visualizing feature maps in PyTorch.
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