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All convolutions in a very dense block are ReLU-activated and use batch normalization. Channel-intelligent concatenation is just attainable if the height and width dimensions of the data stay unchanged, so convolutions inside a dense block are all of stride 1. Pooling levels are inserted between dense blocks for additional dimensionality reduction.