Deep Convolutional Networks with Non-convolutional Recurrent Memory for Structured Prediction

This work proposes and evaluates a memory mechanism enhanced convolutional neural network architecture based on augmenting residual networks (ResNets) with a non-convolutional long short term memory mechanism that yields results comparable to state-of-the-art results on a structured prediction task, but with much fewer parameters and a significantly lower computational cost.