Chinese image caption of Inceptionv4 and double-layer GRUs based on attention mechanism. Issue 1 (March 2021) - Pan, Yongbin; Wang, Lidan; Duan, Shukai; Gan, Xiuling; Hong, Liangyi
Abstract: In recent years, there has been a wave of research on English image caption at home and abroad. However, due to the particularity of Chinese image caption task, the research on Chinese image caption has not made good progress. In order to solve this problem, a new Chinese image caption model is implemented. Firstly, the AI challenge dataset is enhanced, and then the Chinese text data of the dataset is preprocessed by Chinese word segmentation tool word2vec. Secondly, based on the encoder-decoder framework, the image visual features are extracted by Inceptionv4 network, the attention mechanism is incorporated in the process of feature extraction and the Chinese sentences are generated by double-layer GRUs network. In the process of training, Adam is used to optimize the algorithm. Finally, A GUI interface is designed to better show the experimental effect. Experiments show that the new Chinese image caption model can automatically generate more fluent and more accurate Chinese caption sentences, and the trained model has excellent performance in many evaluation indexes.