… Hybrid approaches such as combinations of CNN and LSTM are becoming increasingly popular
… The addition of a CNN to LSTM usually leads to better results compared to a pure LSTM …

… and propose a hybrid model architecture that combines CNNs and LSTM network. To best of
our … In this study, we assessed the ability of the CNN-LSTM network to accurately detect AH …

… , a hybrid 2D CNN-LSTM network incorporating the FL function to deal with data imbalance
is proposed. The network … A similar approach but using a 1D CNN-LSTM architecture with …

… In this study, a hybrid deep learning model is proposed … a hybrid deep learning methodology
that integrates convolutional neural network (CNN) and long short term memory (LSTM) …

… network with Snake Curve network model is significantly improved compared to hybrid
CNN-LSTM network … 6c, the hybrid CNN-LSTM network framework proposed in this paper has …

… and the 1DCNN-LSTM network. The model combined the time expansion of the CNN and
the … the typical methods of RNN series to combine the CNN method with the LSTM method. …

… network combining 3-D CNN, 2-D CNN and Bi-LSTM. Joint spatial–spectral features are
learnt by the 3-D CNN… 3-D and 2-D CNN along with Bi-LSTM layer for the classification of HSI …

… The CNN-LSTM hybrid model is capable of including images … this hybrid model is compared
to the GARCH and LSTM … model, and 18% compared to the LSTM model. Finally, the Model …

… a hybrid DL method is to boost the performance of our integrated production/maintenance
model. We adopt a hybrid DL method that combines the CNN and LSTM networks to predict …

… In conclusion, the hybrid model that is based on CNN and LSTM that we have proposed in
this paper, has shown its effectiveness by giving the best result in four among five evaluation …