implementation of cnn Search Results


cnn implemented in a common planning software  (MediCAD HECTEC)
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MediCAD HECTEC cnn implemented in a common planning software
Cnn Implemented In A Common Planning Software, supplied by MediCAD HECTEC, 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
https://www.bioz.com/result/classifier-based implementation of existing cnn models/product/SoftMax Inc
Average 90 stars, based on 1 article reviews
classifier-based implementation of existing cnn models - by Bioz Stars, 2026-03
90/100 stars
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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: