What is CNN architecture?

What is CNN architecture?

CNN architecture, or Convolutional Neural Network architecture, is a deep learning model primarily used for image processing.

What are the main components of a CNN?

The main components of a CNN include convolutional layers, pooling layers, and fully connected layers.

How does the convolutional layer work?

The convolutional layer applies filters to the input image to extract features, such as edges and textures.

What is the purpose of pooling layers?

Pooling layers reduce the spatial dimensions of the feature maps, helping to decrease computation and control overfitting.

Can you explain how CNNs are used in image classification?

CNNs are used in image classification by learning to identify patterns in images through training on labeled datasets.