Authors: Yejun Tang, Haoyu Qin, Liangrui Peng, Department of Electronic Engineering, Tsinghua University, Beijing, China
Description: A simplified GoogLeNet is used (Caffe implementation). The network is trained by using augmented samples. The original samples in the training set are rotated, blurred, mirrored and inverted. The numbers of training sam- ples of different scripts are balanced. The input images are resized into 256x256 pixels and cropped into 227x227 pixels.