resnet-50 Search Results


resnet50  (SoftMax Inc)
90
SoftMax Inc resnet50
Hyper-parameter settings for different transfer learning models.
Resnet50, 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/resnet-50/resnet50/pmc09046104-25-0-5
Average 90 stars, based on 1 article reviews
resnet50 - by Bioz Stars, 2026-09
90/100 stars
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classifier with resnet-50  (SoftMax Inc)
90
SoftMax Inc classifier with resnet-50
Hyper-parameter settings for different transfer learning models.
Classifier With Resnet 50, 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/resnet-50/classifier+with+resnet+50/pm40596195-375-12-9
Average 90 stars, based on 1 article reviews
classifier with resnet-50 - by Bioz Stars, 2026-09
90/100 stars
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3d-resnet50  (TenCent Inc)
90
TenCent Inc 3d-resnet50
Hyper-parameter settings for different transfer learning models.
3d Resnet50, supplied by TenCent 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/resnet-50/resnet50/ppr0919389-251-2-12
Average 90 stars, based on 1 article reviews
3d-resnet50 - by Bioz Stars, 2026-09
90/100 stars
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deepometry software resnet50  (Broad Institute Inc)
90
Broad Institute Inc deepometry software resnet50
Hyper-parameter settings for different transfer learning models.
Deepometry Software Resnet50, supplied by Broad Institute 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/resnet-50/resnet50+backbone/pmc09404284-226-23-19
Average 90 stars, based on 1 article reviews
deepometry software resnet50 - by Bioz Stars, 2026-09
90/100 stars
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resnet50  (SusTech GmbH)
90
SusTech GmbH resnet50
Hyper-parameter settings for different transfer learning models.
Resnet50, supplied by SusTech GmbH, 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/resnet-50/resnet50+backbone/pmc12082602-94-11-14
Average 90 stars, based on 1 article reviews
resnet50 - by Bioz Stars, 2026-09
90/100 stars
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resnet50  (EyePACS LLC)
90
EyePACS LLC resnet50
Weighted average F1-scores of all trained models on the respective test datasets. For models trained with Differential Privacy, the utilized privacy budget ϵ is given in brackets.
Resnet50, supplied by EyePACS LLC, 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/resnet-50/resnet50/pmc10356902-6-2-0
Average 90 stars, based on 1 article reviews
resnet50 - by Bioz Stars, 2026-09
90/100 stars
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resnet50  (myDATA GmbH)
90
myDATA GmbH resnet50
Weighted average F1-scores of all trained models on the respective test datasets. For models trained with Differential Privacy, the utilized privacy budget ϵ is given in brackets.
Resnet50, supplied by myDATA GmbH, 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/resnet-50/resnet50/10__1088_slash_1742___6596_slash_1937_slash_1_slash_012056-207-137-115
Average 90 stars, based on 1 article reviews
resnet50 - by Bioz Stars, 2026-09
90/100 stars
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resnet50 backbone  (Tecno Chem CO LTD)
90
Tecno Chem CO LTD resnet50 backbone
Weighted average F1-scores of all trained models on the respective test datasets. For models trained with Differential Privacy, the utilized privacy budget ϵ is given in brackets.
Resnet50 Backbone, supplied by Tecno Chem CO LTD, 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/resnet-50/resnet50+backbone/pm38570373-111-10-13
Average 90 stars, based on 1 article reviews
resnet50 backbone - by Bioz Stars, 2026-09
90/100 stars
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resnet50 network  (MVTec Software GmbH)
90
MVTec Software GmbH resnet50 network
Weighted average F1-scores of all trained models on the respective test datasets. For models trained with Differential Privacy, the utilized privacy budget ϵ is given in brackets.
Resnet50 Network, supplied by MVTec Software GmbH, 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/resnet-50/resnet50+network/pmc11397818-78-2-20
Average 90 stars, based on 1 article reviews
resnet50 network - by Bioz Stars, 2026-09
90/100 stars
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resnet-50  (Cadx Systems Inc)
90
Cadx Systems Inc resnet-50
Weighted average F1-scores of all trained models on the respective test datasets. For models trained with Differential Privacy, the utilized privacy budget ϵ is given in brackets.
Resnet 50, 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
https://www.bioz.com/product/resnet-50/resnet+50/pmc10295325-396-34-19
Average 90 stars, based on 1 article reviews
resnet-50 - by Bioz Stars, 2026-09
90/100 stars
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resnet-50  (Johns Hopkins HealthCare)
90
Johns Hopkins HealthCare resnet-50
Weighted average F1-scores of all trained models on the respective test datasets. For models trained with Differential Privacy, the utilized privacy budget ϵ is given in brackets.
Resnet 50, supplied by Johns Hopkins HealthCare, 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/resnet-50/resnet+50/pmc07812355-20-30-22
Average 90 stars, based on 1 article reviews
resnet-50 - by Bioz Stars, 2026-09
90/100 stars
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2d resnet-50  (IEEE Access)
90
IEEE Access 2d resnet-50
Key characteristics of the selected articles.
2d Resnet 50, 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/product/resnet-50/2d+resnet+50/pmc11394591-15-7-26
Average 90 stars, based on 1 article reviews
2d resnet-50 - by Bioz Stars, 2026-09
90/100 stars
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Image Search Results


Hyper-parameter settings for different transfer learning models.

Journal: Computers & Electrical Engineering

Article Title: Internet of Medical Things for early prediction of COVID-19 using ensemble transfer learning ☆

doi: 10.1016/j.compeleceng.2022.108018

Figure Lengend Snippet: Hyper-parameter settings for different transfer learning models.

Article Snippet: ResNet50 (M2) , 100 , Softmax , 16 , Binary crossentropy , Adam , 0.001.

Techniques: Activation Assay

Result of the transfer learning models without using Dropout.

Journal: Computers & Electrical Engineering

Article Title: Internet of Medical Things for early prediction of COVID-19 using ensemble transfer learning ☆

doi: 10.1016/j.compeleceng.2022.108018

Figure Lengend Snippet: Result of the transfer learning models without using Dropout.

Article Snippet: ResNet50 (M2) , 100 , Softmax , 16 , Binary crossentropy , Adam , 0.001.

Techniques:

Result of the transfer learning models with Dropout and a FC connected layer at the end.

Journal: Computers & Electrical Engineering

Article Title: Internet of Medical Things for early prediction of COVID-19 using ensemble transfer learning ☆

doi: 10.1016/j.compeleceng.2022.108018

Figure Lengend Snippet: Result of the transfer learning models with Dropout and a FC connected layer at the end.

Article Snippet: ResNet50 (M2) , 100 , Softmax , 16 , Binary crossentropy , Adam , 0.001.

Techniques:

Result of the transfer learning models with Dropout and two FC layers with 128 and 64 neurons.

Journal: Computers & Electrical Engineering

Article Title: Internet of Medical Things for early prediction of COVID-19 using ensemble transfer learning ☆

doi: 10.1016/j.compeleceng.2022.108018

Figure Lengend Snippet: Result of the transfer learning models with Dropout and two FC layers with 128 and 64 neurons.

Article Snippet: ResNet50 (M2) , 100 , Softmax , 16 , Binary crossentropy , Adam , 0.001.

Techniques:

Result of the transfer learning models without using Dropout and three FC layers with 256, 128, and 64 neurons respectively.

Journal: Computers & Electrical Engineering

Article Title: Internet of Medical Things for early prediction of COVID-19 using ensemble transfer learning ☆

doi: 10.1016/j.compeleceng.2022.108018

Figure Lengend Snippet: Result of the transfer learning models without using Dropout and three FC layers with 256, 128, and 64 neurons respectively.

Article Snippet: ResNet50 (M2) , 100 , Softmax , 16 , Binary crossentropy , Adam , 0.001.

Techniques:

Result of the transfer learning models with Dropout and four FC layers with 512, 256, 128, and 64 neurons respectively and taking their ensemble.

Journal: Computers & Electrical Engineering

Article Title: Internet of Medical Things for early prediction of COVID-19 using ensemble transfer learning ☆

doi: 10.1016/j.compeleceng.2022.108018

Figure Lengend Snippet: Result of the transfer learning models with Dropout and four FC layers with 512, 256, 128, and 64 neurons respectively and taking their ensemble.

Article Snippet: ResNet50 (M2) , 100 , Softmax , 16 , Binary crossentropy , Adam , 0.001.

Techniques:

Average execution time taken by transfer learning models.

Journal: Computers & Electrical Engineering

Article Title: Internet of Medical Things for early prediction of COVID-19 using ensemble transfer learning ☆

doi: 10.1016/j.compeleceng.2022.108018

Figure Lengend Snippet: Average execution time taken by transfer learning models.

Article Snippet: ResNet50 (M2) , 100 , Softmax , 16 , Binary crossentropy , Adam , 0.001.

Techniques:

Weighted average F1-scores of all trained models on the respective test datasets. For models trained with Differential Privacy, the utilized privacy budget ϵ is given in brackets.

Journal: Frontiers in Bioinformatics

Article Title: Translating theory into practice: assessing the privacy implications of concept-based explanations for biomedical AI

doi: 10.3389/fbinf.2023.1194993

Figure Lengend Snippet: Weighted average F1-scores of all trained models on the respective test datasets. For models trained with Differential Privacy, the utilized privacy budget ϵ is given in brackets.

Article Snippet: EyePACS , ResNet50 , 86.72 , 87.39 , 82.29 (05).

Techniques:

Weighted average F1-scores of ResNet50 models trained on ISIC and EyePACS with differential privacy ( ϵ = 10) under different imbalanced training settings.

Journal: Frontiers in Bioinformatics

Article Title: Translating theory into practice: assessing the privacy implications of concept-based explanations for biomedical AI

doi: 10.3389/fbinf.2023.1194993

Figure Lengend Snippet: Weighted average F1-scores of ResNet50 models trained on ISIC and EyePACS with differential privacy ( ϵ = 10) under different imbalanced training settings.

Article Snippet: EyePACS , ResNet50 , 86.72 , 87.39 , 82.29 (05).

Techniques:

Key characteristics of the selected articles.

Journal: Cancers

Article Title: Oncologic Applications of Artificial Intelligence and Deep Learning Methods in CT Spine Imaging—A Systematic Review

doi: 10.3390/cancers16172988

Figure Lengend Snippet: Key characteristics of the selected articles.

Article Snippet: Masoudi S. et al. [ ] , 2D ResNet-50, ResNeXt-50, 3D ResNet-18, 3D ResNet-50 , 2021 , Differentiate benign versus malignant spinal lesions on CT. , IEEE Access , Classification (Benign vs. malignant) , 114 , Accuracy: 79.4–92.2%; F1-Score: 0.755–0.923.

Techniques: Imaging, Expressing, Biomarker Discovery