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kernel cnn

Innocent Iguana answered on May 25, 2023 Popularity 7/10 Helpfulness 4/10

answer kernel cnn

kernel cnn

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- kernels in CNN are learnable parameters
- Each kernel is anologous to each neurons.
- Each kernel is responsible for determining different properties of the image
- Activation functions help the kernels produce activation maps
- usually each output is smaller
- M kernels produce M feature maps
- In the next layer, previous layer's feature maps are accepted as inputs
- Next layer's output feature map is calculated by combining/adding convolution on previous layer's feature maps and activation function
- The deeper the layer, the more complex patterns the kernels capture

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Contributed on May 25 2023

Innocent Iguana

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