cnn-softmax models Search Results


transfer learning-based cnn models  (SoftMax Inc)
90
SoftMax Inc transfer learning-based cnn models
Sorting the selected types-based activations among <t>CNN</t> <t>models</t> by applying the LIME method to the CPB data.
Transfer Learning Based 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
https://www.bioz.com/product/cnn-softmax+models/pmc08410514-311-7-9?v=SoftMax+Inc
Average 90 stars, based on 1 article reviews
transfer learning-based cnn models - by Bioz Stars, 2026-07
90/100 stars
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unsupervised eye contact pipeline/cnn model  (SoftMax Inc)
90
SoftMax Inc unsupervised eye contact pipeline/cnn model
Summary of the existing approaches used for basic and learning-centred emotion classification models.
Unsupervised Eye Contact Pipeline/Cnn 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/product/cnn-softmax+models/pmc10747450-16-13-24?v=SoftMax+Inc
Average 90 stars, based on 1 article reviews
unsupervised eye contact pipeline/cnn model - by Bioz Stars, 2026-07
90/100 stars
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classifier-based implementation of existing cnn models  (SoftMax Inc)
90
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
https://www.bioz.com/product/cnn-softmax+models/pmc08403339-272-22-17?v=SoftMax+Inc
Average 90 stars, based on 1 article reviews
classifier-based implementation of existing cnn models - by Bioz Stars, 2026-07
90/100 stars
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classification layers of 11 pre-trained cnn models  (SoftMax Inc)
90
SoftMax Inc classification layers of 11 pre-trained cnn models
Performance of the developed COVID-19 detection models on the unseen dataset.
Classification Layers Of 11 Pre Trained 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
https://www.bioz.com/product/cnn-softmax+models/10__1016_slash_j__bspc__2023__104603-206-0-0?v=SoftMax+Inc
Average 90 stars, based on 1 article reviews
classification layers of 11 pre-trained cnn models - by Bioz Stars, 2026-07
90/100 stars
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cnn-svm model 2  (SoftMax Inc)
90
SoftMax Inc cnn-svm model 2
Performance of the developed COVID-19 detection models on the unseen dataset.
Cnn Svm Model 2, 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/product/cnn-softmax+models/10__1007_slash_s12206___023___0332___x-130-8-14?v=SoftMax+Inc
Average 90 stars, based on 1 article reviews
cnn-svm model 2 - by Bioz Stars, 2026-07
90/100 stars
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Image Search Results


Sorting the selected types-based activations among CNN models by applying the LIME method to the CPB data.

Journal: Biomedical Signal Processing and Control

Article Title: Detection of COVID-19 findings by the local interpretable model-agnostic explanations method of types-based activations extracted from CNNs

doi: 10.1016/j.bspc.2021.103128

Figure Lengend Snippet: Sorting the selected types-based activations among CNN models by applying the LIME method to the CPB data.

Article Snippet: Before the last layer of transfer learning-based CNN models (pre-Softmax), activation sets as many as the number of class types are formed.

Techniques:

Sorting the selected types-based activations among CNN models by applying the LIME method to the CovCT-Findings data.

Journal: Biomedical Signal Processing and Control

Article Title: Detection of COVID-19 findings by the local interpretable model-agnostic explanations method of types-based activations extracted from CNNs

doi: 10.1016/j.bspc.2021.103128

Figure Lengend Snippet: Sorting the selected types-based activations among CNN models by applying the LIME method to the CovCT-Findings data.

Article Snippet: Before the last layer of transfer learning-based CNN models (pre-Softmax), activation sets as many as the number of class types are formed.

Techniques:

Summary of the existing approaches used for basic and learning-centred emotion classification models.

Journal: Sensors (Basel, Switzerland)

Article Title: Real-Time Robotic Presentation Skill Scoring Using Multi-Model Analysis and Fuzzy Delphi–Analytic Hierarchy Process

doi: 10.3390/s23249619

Figure Lengend Snippet: Summary of the existing approaches used for basic and learning-centred emotion classification models.

Article Snippet: [ ] , × , √ , × , 0 , 0 , Unsupervised eye contact pipeline/CNN Model , Binary support vector machine (SVC) classifier/Softmax , × , CNN Model.

Techniques: Extraction, Plasmid Preparation

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: