Maosen Wang1, Shaozhang Niu1,*, Zhenguang Gao2
CMC-Computers, Materials & Continua, Vol.60, No.2, pp. 781-794, 2019, DOI:10.32604/cmc.2019.05595
Abstract Scene text recognition is one of the most important techniques in pattern recognition and machine intelligence due to its numerous practical applications. Scene text recognition is also a sequence model task. Recurrent neural network (RNN) is commonly regarded as the default starting point for sequential models. Due to the non-parallel prediction and the gradient disappearance problem, the performance of the RNN is difficult to improve substantially. In this paper, a new TRDD network architecture which base on dilated convolution and residual block is proposed, using Convolutional Neural Networks (CNN) instead of RNN realizes the recognition task of sequence texts. Our… More >
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