Authors: IFLYTEK

Description: Description: an attention-based text recognizer is designed as an encoder-decoder framework. In the encoding stage, an image is transformed into a sequence of feature vectors by CNN/LSTM, and each feature vector corresponds to a region in the input image. In the decoding stage, the attention model first computes alignment factors by referring to the history of target characters and the encoded feature vectors for generating the synthesis vectors. Then, a recurrent neural network (RNN) is used to generate the target characters based on the glimpse vectors and the history of target characters.