  This paper proposes a branched residual network for image classification. It
is known that high-level features of deep neural network are more
representative than lower-level features. By sharing the low-level features,
the network can allocate more memory to high-level features. The upper layers
of our proposed network are branched, so that it mimics the ensemble learning.
By mimicking ensemble learning with single network, we have achieved better
performance on ImageNet classification task.
