2 天前 - … This study constructs a hybrid prediction model based on CEEMDAN-LSTM-CNN
for forecasting the potential of reclaimed water, which enhances prediction accuracy and …

3 天前 - … However, there are several attacks that can target CNN-based watermarking
techniques… and extractor network is being employed to ensure that the proposed hybrid network is …

3 天前 - … In this study, the authors present a CNN, a Bi-LSTM neural network, and a CRF
design for … outcomes compared to the baseline approaches of RNN, LSTM, and Bi-LSTM [28]. …

3 天前 - … hybrid model, IChOA-CNN-LSTM, which leverages Convolutional Neural Networks
(CNNs) for precise image feature extraction, Long Short-Term Memory (LSTM) networks for …

3 天前 - … The features of energy consumption present the output of CNN final pooling layer
is used as input to the LSTM network which is indicated using 𝑝:. The combined architecture …

3 天前 - … Neural Network (CNN) untuk ekstraksi ciri visual dari gambar dan Long Short-Term
Memory (LSTM) sebagai pengganti lapisan terakhir dari CNN, … Integrasi CNN dengan LSTM …

5 天前 - … This research proposes a hybrid model for detecting common cyber-attacks using
two … was performed using the LSTM and CNN algorithms as part of the hybrid model. The …

6 天前 - … This study uses a DNN that combines 1D CNN and LSTM to accurately analyze …
this DNN, which also incorporates 1D CNN and LSTM, to classify upcoming reports for …

6 天前 - … Empirical findings reveal that the CNN-LSTM hybrid model surpasses both
traditional forecasting methods and standalone neural network models regarding accuracy and …

6 天前 - … the network’s architecture. The left side of the network consists of two consecutive
LSTM … This vector represents the input data for the CNN part of the network. Similar to an …