softmax-based model Search Results


softmax-based phenomenological model  (SoftMax Inc)
90
SoftMax Inc softmax-based phenomenological model
Softmax Based Phenomenological 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
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fault type model based on softmax classifier  (SoftMax Inc)
90
SoftMax Inc fault type model based on softmax classifier
Fault Type Model Based On Softmax Classifier, 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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beta weights 1st action model based beta  (SoftMax Inc)
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SoftMax Inc beta weights 1st action model based beta
Beta Weights 1st Action Model Based Beta, 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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beta weights 1st action model based beta - by Bioz Stars, 2026-04
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classifier 112 softmax  (SoftMax Inc)
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SoftMax Inc classifier 112 softmax
Classifier 112 Softmax, 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-based model  (SoftMax Inc)
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SoftMax Inc softmax-based model
Softmax Based 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
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softmax-based model - by Bioz Stars, 2026-04
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stacked gru model based on  (SoftMax Inc)
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SoftMax Inc stacked gru model based on
Parameters of the stacked <t> GRU </t> network layers.
Stacked Gru Model Based On, 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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stacked gru model based on - by Bioz Stars, 2026-04
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perceptron-based (pb0) model  (SoftMax Inc)
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SoftMax Inc perceptron-based (pb0) model
Parameters of the stacked <t> GRU </t> network layers.
Perceptron Based (Pb0) 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
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classifier-based implementation of existing cnn models  (SoftMax Inc)
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SoftMax Inc classifier-based implementation of existing cnn models
Performance of the developed COVID-19 detection models on the unseen dataset.
Classifier Based Implementation Of Existing Cnn Models, 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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cbow model based on the hierarchical  (SoftMax Inc)
90
SoftMax Inc cbow model based on the hierarchical
Performance of the developed COVID-19 detection models on the unseen dataset.
Cbow Model Based On The Hierarchical, 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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deep learning based keyword wake-up model  (SoftMax Inc)
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SoftMax Inc deep learning based keyword wake-up model
Performance of the developed COVID-19 detection models on the unseen dataset.
Deep Learning Based Keyword Wake Up 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
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Image Search Results


Parameters of the stacked GRU network layers.

Journal: Expert Systems with Applications

Article Title: Advanced deep learning approaches to predict supply chain risks under COVID-19 restrictions

doi: 10.1016/j.eswa.2022.118604

Figure Lengend Snippet: Parameters of the stacked GRU network layers.

Article Snippet: On the other hand, in it can be seen that the results of the stacked GRU based on KNN showed the highest performance, while the stacked GRU based on ANN and SVM showed the same performance and the stacked GRU based on RT and RF showed the same performance, while the stacked GRU model based on Softmax showed the lowest statistical results performance on the test data. shows the roc curves of the stacked GRU model based on Softmax, RT, RF, KNN, ANN, and SVM classifiers.

Techniques: Sequencing, Activation Assay

Parameters of the training options for the proposed RNN Models.

Journal: Expert Systems with Applications

Article Title: Advanced deep learning approaches to predict supply chain risks under COVID-19 restrictions

doi: 10.1016/j.eswa.2022.118604

Figure Lengend Snippet: Parameters of the training options for the proposed RNN Models.

Article Snippet: On the other hand, in it can be seen that the results of the stacked GRU based on KNN showed the highest performance, while the stacked GRU based on ANN and SVM showed the same performance and the stacked GRU based on RT and RF showed the same performance, while the stacked GRU model based on Softmax showed the lowest statistical results performance on the test data. shows the roc curves of the stacked GRU model based on Softmax, RT, RF, KNN, ANN, and SVM classifiers.

Techniques: Biomarker Discovery

Training and loss curves of the stacked GRU model for shipments prediction.

Journal: Expert Systems with Applications

Article Title: Advanced deep learning approaches to predict supply chain risks under COVID-19 restrictions

doi: 10.1016/j.eswa.2022.118604

Figure Lengend Snippet: Training and loss curves of the stacked GRU model for shipments prediction.

Article Snippet: On the other hand, in it can be seen that the results of the stacked GRU based on KNN showed the highest performance, while the stacked GRU based on ANN and SVM showed the same performance and the stacked GRU based on RT and RF showed the same performance, while the stacked GRU model based on Softmax showed the lowest statistical results performance on the test data. shows the roc curves of the stacked GRU model based on Softmax, RT, RF, KNN, ANN, and SVM classifiers.

Techniques:

The results of the stacked-GRU model on the validation data in terms of various statistical performance measurements.

Journal: Expert Systems with Applications

Article Title: Advanced deep learning approaches to predict supply chain risks under COVID-19 restrictions

doi: 10.1016/j.eswa.2022.118604

Figure Lengend Snippet: The results of the stacked-GRU model on the validation data in terms of various statistical performance measurements.

Article Snippet: On the other hand, in it can be seen that the results of the stacked GRU based on KNN showed the highest performance, while the stacked GRU based on ANN and SVM showed the same performance and the stacked GRU based on RT and RF showed the same performance, while the stacked GRU model based on Softmax showed the lowest statistical results performance on the test data. shows the roc curves of the stacked GRU model based on Softmax, RT, RF, KNN, ANN, and SVM classifiers.

Techniques: Biomarker Discovery

ROC of the stacked GRU model using various classifiers on the shipments test data prediction.

Journal: Expert Systems with Applications

Article Title: Advanced deep learning approaches to predict supply chain risks under COVID-19 restrictions

doi: 10.1016/j.eswa.2022.118604

Figure Lengend Snippet: ROC of the stacked GRU model using various classifiers on the shipments test data prediction.

Article Snippet: On the other hand, in it can be seen that the results of the stacked GRU based on KNN showed the highest performance, while the stacked GRU based on ANN and SVM showed the same performance and the stacked GRU based on RT and RF showed the same performance, while the stacked GRU model based on Softmax showed the lowest statistical results performance on the test data. shows the roc curves of the stacked GRU model based on Softmax, RT, RF, KNN, ANN, and SVM classifiers.

Techniques:

Confusion matrix of the stacked GRU model using various classifiers on the shipments test data prediction.

Journal: Expert Systems with Applications

Article Title: Advanced deep learning approaches to predict supply chain risks under COVID-19 restrictions

doi: 10.1016/j.eswa.2022.118604

Figure Lengend Snippet: Confusion matrix of the stacked GRU model using various classifiers on the shipments test data prediction.

Article Snippet: On the other hand, in it can be seen that the results of the stacked GRU based on KNN showed the highest performance, while the stacked GRU based on ANN and SVM showed the same performance and the stacked GRU based on RT and RF showed the same performance, while the stacked GRU model based on Softmax showed the lowest statistical results performance on the test data. shows the roc curves of the stacked GRU model based on Softmax, RT, RF, KNN, ANN, and SVM classifiers.

Techniques:

The results of the stacked-GRU model on the test data in terms of various statistical performance measurements.

Journal: Expert Systems with Applications

Article Title: Advanced deep learning approaches to predict supply chain risks under COVID-19 restrictions

doi: 10.1016/j.eswa.2022.118604

Figure Lengend Snippet: The results of the stacked-GRU model on the test data in terms of various statistical performance measurements.

Article Snippet: On the other hand, in it can be seen that the results of the stacked GRU based on KNN showed the highest performance, while the stacked GRU based on ANN and SVM showed the same performance and the stacked GRU based on RT and RF showed the same performance, while the stacked GRU model based on Softmax showed the lowest statistical results performance on the test data. shows the roc curves of the stacked GRU model based on Softmax, RT, RF, KNN, ANN, and SVM classifiers.

Techniques:

Performance of the developed COVID-19 detection models on the unseen dataset.

Journal: Computers in Biology and Medicine

Article Title: COVID-19 detection in chest X-ray images using deep boosted hybrid learning

doi: 10.1016/j.compbiomed.2021.104816

Figure Lengend Snippet: Performance of the developed COVID-19 detection models on the unseen dataset.

Article Snippet: To identify the significance of exploitation of deep feature engineering, for comparison purposes, we have used a Softmax classifier-based implementation of existing CNN models as well.

Techniques:

Performance comparison of hybrid based DHL and Softmax classifier-based implementation of well-established CNN models.

Journal: Computers in Biology and Medicine

Article Title: COVID-19 detection in chest X-ray images using deep boosted hybrid learning

doi: 10.1016/j.compbiomed.2021.104816

Figure Lengend Snippet: Performance comparison of hybrid based DHL and Softmax classifier-based implementation of well-established CNN models.

Article Snippet: To identify the significance of exploitation of deep feature engineering, for comparison purposes, we have used a Softmax classifier-based implementation of existing CNN models as well.

Techniques: Comparison

ROC curve for the proposed frameworks (DHL, DBHL), the developed and well-established CNN Models. The square bracket values represent the tolerance or error, calculated at a 95% confidence interval .

Journal: Computers in Biology and Medicine

Article Title: COVID-19 detection in chest X-ray images using deep boosted hybrid learning

doi: 10.1016/j.compbiomed.2021.104816

Figure Lengend Snippet: ROC curve for the proposed frameworks (DHL, DBHL), the developed and well-established CNN Models. The square bracket values represent the tolerance or error, calculated at a 95% confidence interval .

Article Snippet: To identify the significance of exploitation of deep feature engineering, for comparison purposes, we have used a Softmax classifier-based implementation of existing CNN models as well.

Techniques: