2d-cnn Search Results


90
SoftMax Inc 2d-cnn
2d Cnn, 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
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SoftMax Inc 2d-cnn with 1d-cnn
Summary of related works done using 2D-CNNs.
2d Cnn With 1d Cnn, 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
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90
Tanabe 2d-cnn
Summary of related works done using 2D-CNNs.
2d Cnn, supplied by Tanabe, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Beuth Verlag GmbH 2d cnn
Summary of related works done using 2D-CNNs.
2d Cnn, supplied by Beuth Verlag GmbH, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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IEEE Access 2d cnn
Summary of related works done using 2D-CNNs.
2d Cnn, 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
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90
ASHRAE Inc 2-d cnn
Supervised learning used in the research from the selected literature. If the record contains a certain value for Software, then it is actually a representative of a hybrid approach in which some of the data-driven techniques are implemented. For clarity, all acronyms are provided in the Abbreviations list.
2 D Cnn, supplied by ASHRAE Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Mendeley Ltd k-mean ++, 2d cnn, 3d cnn and gbdt
Inlustraions <t>of</t> <t>2D</t> CNN and <t>GBDT</t> models (A) Schematic overview of the 2D CNN model. Four convolutional layers and four max pooling layers are included in the 2D CNN model. Here, the kernel size of each convolutional layer is set to be three and the pooling size is two. (B) Illustration of GBDT model with N gradient boosting trees.
K Mean ++, 2d Cnn, 3d Cnn And Gbdt, supplied by Mendeley Ltd, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Kaggle Inc sigmoid, 2d cnn-lstm
A review of recent research that applied the CNN-RNNs model for seizure prediction with their corresponding accuracies.
Sigmoid, 2d 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
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Photonics Inc 2d-cnn equalization
A review of recent research that applied the CNN-RNNs model for seizure prediction with their corresponding accuracies.
2d Cnn Equalization, supplied by Photonics Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Cadx Systems Inc 2d cnn based cadx systems
A review of recent research that applied the CNN-RNNs model for seizure prediction with their corresponding accuracies.
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Hanbay Inc 2d cnn
A review of recent research that applied the CNN-RNNs model for seizure prediction with their corresponding accuracies.
2d Cnn, supplied by Hanbay Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Cadx Systems Inc 2d cnn
A review of recent research that applied the CNN-RNNs model for seizure prediction with their corresponding accuracies.
2d Cnn, supplied by Cadx Systems Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Image Search Results


Summary of related works done using 2D-CNNs.

Journal: International Journal of Environmental Research and Public Health

Article Title: Epileptic Seizures Detection Using Deep Learning Techniques: A Review

doi: 10.3390/ijerph18115780

Figure Lengend Snippet: Summary of related works done using 2D-CNNs.

Article Snippet: [ ] , 2D-CNN with 1D-CNN , 12 , Softmax , NA.

Techniques:

Supervised learning used in the research from the selected literature. If the record contains a certain value for Software, then it is actually a representative of a hybrid approach in which some of the data-driven techniques are implemented. For clarity, all acronyms are provided in the Abbreviations list.

Journal: Sensors (Basel, Switzerland)

Article Title: A Review of Data-Driven Approaches and Techniques for Fault Detection and Diagnosis in HVAC Systems

doi: 10.3390/s23010001

Figure Lengend Snippet: Supervised learning used in the research from the selected literature. If the record contains a certain value for Software, then it is actually a representative of a hybrid approach in which some of the data-driven techniques are implemented. For clarity, all acronyms are provided in the Abbreviations list.

Article Snippet: AHU , 2-D CNN , ASHRAE 1043-RP , , , 2021 , [ ] .

Techniques: Software

Brief summary of related work addressing the hybrid approach in HVAC FDD. For clarity, all acronyms are provided in the Abbreviations list.

Journal: Sensors (Basel, Switzerland)

Article Title: A Review of Data-Driven Approaches and Techniques for Fault Detection and Diagnosis in HVAC Systems

doi: 10.3390/s23010001

Figure Lengend Snippet: Brief summary of related work addressing the hybrid approach in HVAC FDD. For clarity, all acronyms are provided in the Abbreviations list.

Article Snippet: AHU , 2-D CNN , ASHRAE 1043-RP , , , 2021 , [ ] .

Techniques: Software

Inlustraions of 2D CNN and GBDT models (A) Schematic overview of the 2D CNN model. Four convolutional layers and four max pooling layers are included in the 2D CNN model. Here, the kernel size of each convolutional layer is set to be three and the pooling size is two. (B) Illustration of GBDT model with N gradient boosting trees.

Journal: iScience

Article Title: Deep learning-enabled quantification of simultaneous PET/MRI for cell transplantation monitoring

doi: 10.1016/j.isci.2023.107083

Figure Lengend Snippet: Inlustraions of 2D CNN and GBDT models (A) Schematic overview of the 2D CNN model. Four convolutional layers and four max pooling layers are included in the 2D CNN model. Here, the kernel size of each convolutional layer is set to be three and the pooling size is two. (B) Illustration of GBDT model with N gradient boosting trees.

Article Snippet: Codes for K-mean ++, 2D CNN, 3D CNN and GBDT , This paper; Mendeley Data , https://doi.org/10.17632/995vjkhm68.1.

Techniques:

Comparison, testing, and training of 3D CNN (A) Bar graph showing comparison of predictive performance of the 3D CNN, 2D CNN, and GBDT algorithms via analysis of root mean squared error (RMSE) and mean absolute error (MAE) (∗p < 0.05, ∗∗p < 0.05, the Student’s t test). (B) Bar graph showing comparison of Pearson correlation coefficient (PCC) values between 3D CNN, 2D CNN, and GBDT algorithms. (C) Loss graph of ten training rounds (iterations) comparing the 3D CNN and 2D CNN for both dataset 1 and dataset 2. (D) Intraclass correlation coefficient analysis of 3D CNN’s predictive accuracy on a range of images with 0 to 70μCi radioactivity (∗p = 0.001, ∗∗p = 0.001, the F test).

Journal: iScience

Article Title: Deep learning-enabled quantification of simultaneous PET/MRI for cell transplantation monitoring

doi: 10.1016/j.isci.2023.107083

Figure Lengend Snippet: Comparison, testing, and training of 3D CNN (A) Bar graph showing comparison of predictive performance of the 3D CNN, 2D CNN, and GBDT algorithms via analysis of root mean squared error (RMSE) and mean absolute error (MAE) (∗p < 0.05, ∗∗p < 0.05, the Student’s t test). (B) Bar graph showing comparison of Pearson correlation coefficient (PCC) values between 3D CNN, 2D CNN, and GBDT algorithms. (C) Loss graph of ten training rounds (iterations) comparing the 3D CNN and 2D CNN for both dataset 1 and dataset 2. (D) Intraclass correlation coefficient analysis of 3D CNN’s predictive accuracy on a range of images with 0 to 70μCi radioactivity (∗p = 0.001, ∗∗p = 0.001, the F test).

Article Snippet: Codes for K-mean ++, 2D CNN, 3D CNN and GBDT , This paper; Mendeley Data , https://doi.org/10.17632/995vjkhm68.1.

Techniques: Comparison, Radioactivity

Journal: iScience

Article Title: Deep learning-enabled quantification of simultaneous PET/MRI for cell transplantation monitoring

doi: 10.1016/j.isci.2023.107083

Figure Lengend Snippet:

Article Snippet: Codes for K-mean ++, 2D CNN, 3D CNN and GBDT , This paper; Mendeley Data , https://doi.org/10.17632/995vjkhm68.1.

Techniques: Recombinant, Software

A review of recent research that applied the CNN-RNNs model for seizure prediction with their corresponding accuracies.

Journal: Computational Intelligence and Neuroscience

Article Title: EEG-Based Epileptic Seizure Detection via Machine/Deep Learning Approaches: A Systematic Review

doi: 10.1155/2022/6486570

Figure Lengend Snippet: A review of recent research that applied the CNN-RNNs model for seizure prediction with their corresponding accuracies.

Article Snippet: Roy et al. [ ] , Sigmoid, 2D CNN-LSTM , Time-frequency domain feature , Kaggle , Sen, spec , High training time , 93.00.

Techniques: Selection