This document discusses different convolutional neural network architectures including traditional architectures using convolutional, pooling, and fully connected layers, siamese networks for learning visual similarity, dense prediction networks for tasks like semantic segmentation and image colorization, video classification networks, music recommendation networks, and networks for tasks like object localization, detection, and alignment. It provides examples of specific networks that have been applied to each type of architecture.
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