Zusammenfassung
Basing on the analysis by revealing the equivalence of modern networks, we
find that both ResNet and DenseNet are essentially derived from the same "dense
topology", yet they only differ in the form of connection -- addition (dubbed
"inner link") vs. concatenation (dubbed öuter link"). However, both two forms
of connections have the superiority and insufficiency. To combine their
advantages and avoid certain limitations on representation learning, we present
a highly efficient and modularized Mixed Link Network (MixNet) which is
equipped with flexible inner link and outer link modules. Consequently, ResNet,
DenseNet and Dual Path Network (DPN) can be regarded as a special case of
MixNet, respectively. Furthermore, we demonstrate that MixNets can achieve
superior efficiency in parameter over the state-of-the-art architectures on
many competitive datasets like CIFAR-10/100, SVHN and ImageNet.
Nutzer