lstm Search Results


lstm 64-64  (SoftMax Inc)
90
SoftMax Inc lstm 64-64
Lstm 64 64, supplied by SoftMax Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/lstm 64-64/product/SoftMax Inc
Average 90 stars, based on 1 article reviews
lstm 64-64 - by Bioz Stars, 2026-03
90/100 stars
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lstm layer (64 filters)  (SoftMax Inc)
90
SoftMax Inc lstm layer (64 filters)
Lstm Layer (64 Filters), supplied by SoftMax Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/lstm layer (64 filters)/product/SoftMax Inc
Average 90 stars, based on 1 article reviews
lstm layer (64 filters) - by Bioz Stars, 2026-03
90/100 stars
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cnn based model  (IEEE Access)
90
IEEE Access cnn based model
Cnn Based Model, supplied by IEEE Access, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/cnn based model/product/IEEE Access
Average 90 stars, based on 1 article reviews
cnn based model - by Bioz Stars, 2026-03
90/100 stars
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lstm  (SoftMax Inc)
90
SoftMax Inc lstm
Lstm, supplied by SoftMax Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/lstm/product/SoftMax Inc
Average 90 stars, based on 1 article reviews
lstm - by Bioz Stars, 2026-03
90/100 stars
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deep learning model  (Toshniwal Hyvac)
90
Toshniwal Hyvac deep learning model
Deep Learning Model, supplied by Toshniwal Hyvac, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/deep learning model/product/Toshniwal Hyvac
Average 90 stars, based on 1 article reviews
deep learning model - by Bioz Stars, 2026-03
90/100 stars
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capso-lstm  (Capso Vision Inc)
90
Capso Vision Inc capso-lstm
The image depicts an <t>LSTM</t> (long short-term memory) neural network architecture, illustrating the flow and transformation of data within. It shows the internal gating mechanisms—forget, input, and output gates—of an LSTM cell, how they process the input X, and generate an output Y. The LSTM layer connects to a fully connected layer that integrates the features, leading to the final output layer where the result is produced.
Capso Lstm, supplied by Capso Vision Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/capso-lstm/product/Capso Vision Inc
Average 90 stars, based on 1 article reviews
capso-lstm - by Bioz Stars, 2026-03
90/100 stars
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dnn-bi-lstm classifier  (Enron Corporation)
90
Enron Corporation dnn-bi-lstm classifier
The image depicts an <t>LSTM</t> (long short-term memory) neural network architecture, illustrating the flow and transformation of data within. It shows the internal gating mechanisms—forget, input, and output gates—of an LSTM cell, how they process the input X, and generate an output Y. The LSTM layer connects to a fully connected layer that integrates the features, leading to the final output layer where the result is produced.
Dnn Bi Lstm Classifier, supplied by Enron Corporation, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/dnn-bi-lstm classifier/product/Enron Corporation
Average 90 stars, based on 1 article reviews
dnn-bi-lstm classifier - by Bioz Stars, 2026-03
90/100 stars
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duration-controlled lstm  (Takeda)
90
Takeda duration-controlled lstm
The image depicts an <t>LSTM</t> (long short-term memory) neural network architecture, illustrating the flow and transformation of data within. It shows the internal gating mechanisms—forget, input, and output gates—of an LSTM cell, how they process the input X, and generate an output Y. The LSTM layer connects to a fully connected layer that integrates the features, leading to the final output layer where the result is produced.
Duration Controlled Lstm, supplied by Takeda, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/duration-controlled lstm/product/Takeda
Average 90 stars, based on 1 article reviews
duration-controlled lstm - by Bioz Stars, 2026-03
90/100 stars
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parking occupancy prediction method based on multi factors and stacked gru-lstm  (IEEE Access)
90
IEEE Access parking occupancy prediction method based on multi factors and stacked gru-lstm
The image depicts an <t>LSTM</t> (long short-term memory) neural network architecture, illustrating the flow and transformation of data within. It shows the internal gating mechanisms—forget, input, and output gates—of an LSTM cell, how they process the input X, and generate an output Y. The LSTM layer connects to a fully connected layer that integrates the features, leading to the final output layer where the result is produced.
Parking Occupancy Prediction Method Based On Multi Factors And Stacked Gru Lstm, supplied by IEEE Access, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/parking occupancy prediction method based on multi factors and stacked gru-lstm/product/IEEE Access
Average 90 stars, based on 1 article reviews
parking occupancy prediction method based on multi factors and stacked gru-lstm - by Bioz Stars, 2026-03
90/100 stars
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standard lstm  (SoftMax Inc)
90
SoftMax Inc standard lstm
The image depicts an <t>LSTM</t> (long short-term memory) neural network architecture, illustrating the flow and transformation of data within. It shows the internal gating mechanisms—forget, input, and output gates—of an LSTM cell, how they process the input X, and generate an output Y. The LSTM layer connects to a fully connected layer that integrates the features, leading to the final output layer where the result is produced.
Standard Lstm, supplied by SoftMax Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/standard lstm/product/SoftMax Inc
Average 90 stars, based on 1 article reviews
standard lstm - by Bioz Stars, 2026-03
90/100 stars
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bi-directional lstm model  (SoftMax Inc)
90
SoftMax Inc bi-directional lstm model
The image depicts an <t>LSTM</t> (long short-term memory) neural network architecture, illustrating the flow and transformation of data within. It shows the internal gating mechanisms—forget, input, and output gates—of an LSTM cell, how they process the input X, and generate an output Y. The LSTM layer connects to a fully connected layer that integrates the features, leading to the final output layer where the result is produced.
Bi Directional Lstm Model, supplied by SoftMax Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/bi-directional lstm model/product/SoftMax Inc
Average 90 stars, based on 1 article reviews
bi-directional lstm model - by Bioz Stars, 2026-03
90/100 stars
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bitcoin tweets sentiment analysis: cnn-lstm  (Kaggle Inc)
90
Kaggle Inc bitcoin tweets sentiment analysis: cnn-lstm
The image depicts an <t>LSTM</t> (long short-term memory) neural network architecture, illustrating the flow and transformation of data within. It shows the internal gating mechanisms—forget, input, and output gates—of an LSTM cell, how they process the input X, and generate an output Y. The LSTM layer connects to a fully connected layer that integrates the features, leading to the final output layer where the result is produced.
Bitcoin Tweets Sentiment Analysis: Cnn Lstm, supplied by Kaggle Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/bitcoin tweets sentiment analysis: cnn-lstm/product/Kaggle Inc
Average 90 stars, based on 1 article reviews
bitcoin tweets sentiment analysis: cnn-lstm - by Bioz Stars, 2026-03
90/100 stars
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Image Search Results


The image depicts an LSTM (long short-term memory) neural network architecture, illustrating the flow and transformation of data within. It shows the internal gating mechanisms—forget, input, and output gates—of an LSTM cell, how they process the input X, and generate an output Y. The LSTM layer connects to a fully connected layer that integrates the features, leading to the final output layer where the result is produced.

Journal: PeerJ Computer Science

Article Title: A cosine adaptive particle swarm optimization based long-short term memory method for urban green area prediction

doi: 10.7717/peerj-cs.2048

Figure Lengend Snippet: The image depicts an LSTM (long short-term memory) neural network architecture, illustrating the flow and transformation of data within. It shows the internal gating mechanisms—forget, input, and output gates—of an LSTM cell, how they process the input X, and generate an output Y. The LSTM layer connects to a fully connected layer that integrates the features, leading to the final output layer where the result is produced.

Article Snippet: The Cosine Adaptive Particle Swarm Optimization (CAPSO)-LSTM is used in urban green area prediction, and experimental results demonstrate that the proposed CAPSO-LSTM can accurately predict the area of urban green spaces, providing significant assistance in urban construction planning.

Techniques: Transformation Assay, Produced

The process begins with normalizing the input data, followed by initializing the particle velocity and position. It then calculates the particle fitness and checks if the predefined number of iterations has been reached. If not, it updates the individual and global optima using CAPSO. This loop continues until the iteration condition is met. Once completed, the process outputs the optimal parameters for the LSTM model, which are then used to predict the green area. The flow is sequential and iterative, with a decision point that loops back until the stopping criterion is satisfied.

Journal: PeerJ Computer Science

Article Title: A cosine adaptive particle swarm optimization based long-short term memory method for urban green area prediction

doi: 10.7717/peerj-cs.2048

Figure Lengend Snippet: The process begins with normalizing the input data, followed by initializing the particle velocity and position. It then calculates the particle fitness and checks if the predefined number of iterations has been reached. If not, it updates the individual and global optima using CAPSO. This loop continues until the iteration condition is met. Once completed, the process outputs the optimal parameters for the LSTM model, which are then used to predict the green area. The flow is sequential and iterative, with a decision point that loops back until the stopping criterion is satisfied.

Article Snippet: The Cosine Adaptive Particle Swarm Optimization (CAPSO)-LSTM is used in urban green area prediction, and experimental results demonstrate that the proposed CAPSO-LSTM can accurately predict the area of urban green spaces, providing significant assistance in urban construction planning.

Techniques:

Prediction results of LSTM, PSO-LSTM and CAPSO-LSTM.

Journal: PeerJ Computer Science

Article Title: A cosine adaptive particle swarm optimization based long-short term memory method for urban green area prediction

doi: 10.7717/peerj-cs.2048

Figure Lengend Snippet: Prediction results of LSTM, PSO-LSTM and CAPSO-LSTM.

Article Snippet: The Cosine Adaptive Particle Swarm Optimization (CAPSO)-LSTM is used in urban green area prediction, and experimental results demonstrate that the proposed CAPSO-LSTM can accurately predict the area of urban green spaces, providing significant assistance in urban construction planning.

Techniques:

Results of mean absolute error (MAE), root mean square error (RMSE) and mean absolute percentage error (MAPE).

Journal: PeerJ Computer Science

Article Title: A cosine adaptive particle swarm optimization based long-short term memory method for urban green area prediction

doi: 10.7717/peerj-cs.2048

Figure Lengend Snippet: Results of mean absolute error (MAE), root mean square error (RMSE) and mean absolute percentage error (MAPE).

Article Snippet: The Cosine Adaptive Particle Swarm Optimization (CAPSO)-LSTM is used in urban green area prediction, and experimental results demonstrate that the proposed CAPSO-LSTM can accurately predict the area of urban green spaces, providing significant assistance in urban construction planning.

Techniques:

The black line indicates the predicted values generated by an LSTM model, while the green line represents the actual observed values.

Journal: PeerJ Computer Science

Article Title: A cosine adaptive particle swarm optimization based long-short term memory method for urban green area prediction

doi: 10.7717/peerj-cs.2048

Figure Lengend Snippet: The black line indicates the predicted values generated by an LSTM model, while the green line represents the actual observed values.

Article Snippet: The Cosine Adaptive Particle Swarm Optimization (CAPSO)-LSTM is used in urban green area prediction, and experimental results demonstrate that the proposed CAPSO-LSTM can accurately predict the area of urban green spaces, providing significant assistance in urban construction planning.

Techniques: Generated

The black line indicates the predicted values generated by an CAPSO-LSTM model, while the purple line represents the actual observed values.

Journal: PeerJ Computer Science

Article Title: A cosine adaptive particle swarm optimization based long-short term memory method for urban green area prediction

doi: 10.7717/peerj-cs.2048

Figure Lengend Snippet: The black line indicates the predicted values generated by an CAPSO-LSTM model, while the purple line represents the actual observed values.

Article Snippet: The Cosine Adaptive Particle Swarm Optimization (CAPSO)-LSTM is used in urban green area prediction, and experimental results demonstrate that the proposed CAPSO-LSTM can accurately predict the area of urban green spaces, providing significant assistance in urban construction planning.

Techniques: Generated