12. The method of claim 11 , wherein the decoding of the distributive representation for each of the candidate regions into the one or more output representations includes applying a second recurrent neural network by the decoding module.
12. The method of claim 11 , wherein the decoding of the distributive representation for each of the candidate regions into the one or more output representations includes applying a second recurrent neural network by the decoding module. 13. The method of claim 12 , wherein the first recurrent neural network includes a first LSTM-based recurrent neural network and the second recurrent neural network includes a second LSTM-based recurrent neural network, wherein the first LSTM-based recurrent neural network differs from the second LSTM-based recurrent neural network.