This repository implements the the encoder and decoder model with attention model for OCR, the encoder uses CNN+Bi-LSTM, the decoder uses GRU.

Accurate prediction of future observations based on past data is the key to near real-time disturbance detection using satellite image time series (SITS). To overcome the limitations of existing ...

natural-language-generation document-summarization lstm-neural-network bi-lstm-model encoder-decoder-attention. Updated Nov 28, 2020; r-b6 / Im2Latex. Star 0. Code Issues Pull requests PyTorch model ...

Previously encoder-decoder models were used for machine translation. The encoder-decoder model contains two networks encoder and decoder. The encoder model encodes the input sequence into a vector.

Attention has several advantages over the basic LSTM sequence to sequence model, such as improved handling of long sequences and improved quality and diversity of output.