Convolutional Neural Networks (CNNs) are a specialized class of deep learning algorithms designed to process and analyze visual data, such as images and videos. They are particularly effective for tasks like image classification, object detection, and segmentation. CNNs consist of multiple layers, including convolutional layers that apply filters to input data, pooling layers that reduce dimensionality, and fully connected layers that perform classification based on the extracted features. This architecture enables CNNs to automatically learn hierarchical feature representations, making them highly efficient for visual recognition tasks.
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