  On general object recognition, Deep Convolutional Neural Networks (DCNNs)
achieve high accuracy. In particular, ResNet and its improvements have broken
the lowest error rate records. In this paper, we propose a method to
successfully combine two ResNet improvements, ResDrop and PyramidNet. We
confirmed that the proposed network outperformed the conventional methods; on
CIFAR-100, the proposed network achieved an error rate of 16.18% in contrast to
PiramidNet achieving that of 18.29% and ResNeXt 17.31%.
