Residual Recurrent Neural Network with Sparse Training for Offline Arabic Handwriting Recognition

• Published in: 2017 14th IAPR International Conference on Document Analysis and Recognition (ICDAR) Vol. 1; pp. 1031 - 1037
• Main Authors: Ruijie Yan, Liangrui Peng, GuangXiang Bin, Shengjin Wang, Yao Cheng
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.11.2017
• Subjects: Error analysis; Hidden Markov models; Mathematical model; Recurrent neural networks; Training

Deep Recurrent Neural Networks (RNN) have been suffering from the overfitting problem due to the model redundancy of the network structures. We propose a novel temporal and spatial residual learning method for RNN, followed with sparse training by weight pruning to gain sparsity in network parameter...