Sure, a practical example of the use of convolutional neural networks is in image classification. For instance, given a set of labeled images of objects such as cats, dogs, cars, etc., a convolutional neural network can be trained to identify which object is in a new, unseen image. The network does this by learning to recognize key features of the objects in the training images, such as edges, corners, textures, and so on, which are then detected in the new image and used to make a prediction.
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