February 2018
Intermediate to advanced
378 pages
10h 14m
English
Content preview from Machine Learning with Swift
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CondenseNet
CondenseNet was proposed by Gao Huang, Shichen Liu, Laurens van der Maaten, and Kilian Q. Weinberger. It reaches unprecedented levels of efficiency by combining dense connectivity between layers with a mechanism to remove unused connections, and therefore enables reuse of features within the network. CondenseNet is believed to be much more efficient than the state-of-the-art compact convolutional networks, such as MobileNets and ShuffleNets.
Refer to this: CondenseNet: An Efficient DenseNet using Learned Group Convolutions, Gao Huang, Shichen Liu, Laurens van der Maaten, Kilian Q. Weinberger, November 25, 2017: https://arxiv.org/abs/1711.09224.
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