Chinese Academy of Sciences

Huawei Technologies Co., Limited

Singapore Ze&z International Pte. Ltd

Shenzhen Eulikan Biotechnology Co., Ltd

Wenyong Zhang

Shuqiang Wang

Yanyan Shen

Zhongming Zeng

Kongyuan Wu

The present disclosure relates to an enhanced generative adversarial network and a target sample recognition method. The enhanced generative adversarial network in the present disclosure includes at least one enhanced generator and at least one enhanced discriminator, where the enhanced generator obtains generated data by processing initial data, and provides the generated data to the enhanced discriminator; the enhanced discriminator processes the generated data and feeds back a classification result to the enhanced generator; the enhanced discriminator includes: a convolution layer, a basic capsule layer, a convolution capsule layer, and a classification capsule layer, and the convolution layer, the basic capsule layer, the convolution capsule layer, and the classification capsule layer are sequentially connected to each other.

Enhanced generative adversarial network and target sample recognition method

Growing community of inventors

SHENZHEN, China

Wenyong Zhang