Convolutional Neural Networks (CNNs) are a class of deep learning algorithms commonly used in image recognition and classification tasks.
Key Components of CNNs:
1. Convolutional Layers: These layers apply filters to the input image, capturing essential features such as edges, textures, and patterns.
2. Pooling Layers: These layers reduce the spatial dimensions of the data, simplifying computations and highlighting dominant features.
3. Fully Connected Layers: Located at the end of the network, these layers interpret the extracted features to make final predictions or classifications.
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