A deep network structure is formed with LSTM layer and convolutional layer interweaves with each other. The Layerwise Interweaving Convolutional LSTM (LIC-LSTM) enhanced the feature extraction ability of LSTM stack and is capable for versatile sequential data modeling. Its unique network structure allows it to extract higher level features with sequential information involved. Experiment results show the model achieves higher accuracy and shoulders lower perplexity on sequential data modeling tasks compared with state of art LSTM models.
CITATION STYLE
Duan, T., & Srihari, S. N. (2017). Layerwise interweaving convolutional LSTM. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10233 LNAI, pp. 272–277). Springer Verlag. https://doi.org/10.1007/978-3-319-57351-9_31
Mendeley helps you to discover research relevant for your work.