In the context of Convolutional Neural Networks (CNNs) used for image recognition tasks, what is the primary advantage of incorporating convolutional layers into the architecture? How do these layers help capture meaningful features and patterns from images effectively?
Tarek Berghout
Convolutional layer is generally used to produce a new feature space with (i) less dimensions and (ii) more meaningful representation then the original one by:
1. Detect local patterns by involving small sliding filter over the input data and performing dot products with the filet weights.
2. Reduce the number of input parameters compared to fully connected input layers by sharing weights across spatial dimensions.
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