To solve the problems faced by Chinese character recognition, such as complex shapes and diverse structures, this paper adopts the Visual Geometry Group 16 (VGG-16) model for feature extraction and introduces a two-layer bidirectional Long Short-Term Memory (LSTM) network. It improves the Faster Region-based Convolutional Neural Network (Faster R-CNN) by using a Region Proposal Network (RPN) to extract candidate boxes and adjust the positions of candidate regions. The improved model, namely Faster BLSTM-CNN, is tested through three types of experiments: validation of feature extraction effectiveness, comparative analysis of the algorithm before and after improvement, and comparison with trad... More >