base cnn model Search Results


cnn based model  (IEEE Access)
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modified skip connection-based cnn model  (Kaggle Inc)
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Kaggle Inc modified skip connection-based cnn model
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xception cnn architecture-based cnn model  (Aslan Pharmaceuticals)
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Aslan Pharmaceuticals xception cnn architecture-based cnn model
Comparison of the recommended VGGCOV19-NET COVID-19 diagnosis method with other <t> CNN </t> methods developed using radiology images
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cnn-based model demnet  (Kaggle Inc)
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Kaggle Inc cnn-based model demnet
Comparison between this work and previous studies.
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matlab r2020b  (MathWorks Inc)
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MathWorks Inc matlab r2020b
Comparison between this work and previous studies.
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cnn-based models for quantification of nash histological features  (PathAI Inc)
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PathAI Inc cnn-based models for quantification of nash histological features

Cnn Based Models For Quantification Of Nash Histological Features, supplied by PathAI 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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mask r-cnn deep learning model  (Esri inc)
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Esri inc mask r-cnn deep learning model

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transfer learning-based cnn models  (SoftMax Inc)
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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
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2d-cnn-based model  (MathWorks Inc)
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MathWorks Inc 2d-cnn-based model
Sorting the selected types-based activations among <t>CNN</t> <t>models</t> by applying the LIME method to the CPB data.
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matlab r2020a  (MathWorks Inc)
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Sorting the selected types-based activations among <t>CNN</t> <t>models</t> by applying the LIME method to the CPB data.
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panoptes-based multi-resolution cnn models  (Panoptes Pharma GmbH)
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Panoptes Pharma GmbH panoptes-based multi-resolution cnn models
Sorting the selected types-based activations among <t>CNN</t> <t>models</t> by applying the LIME method to the CPB data.
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hybrid cnn-cat-boost model  (IEEE Access)
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IEEE Access hybrid cnn-cat-boost model
Sorting the selected types-based activations among <t>CNN</t> <t>models</t> by applying the LIME method to the CPB data.
Hybrid Cnn Cat Boost Model, 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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Image Search Results


Comparison of the recommended VGGCOV19-NET COVID-19 diagnosis method with other CNN methods developed using radiology images

Journal: Neural Computing & Applications

Article Title: VGGCOV19-NET: automatic detection of COVID-19 cases from X-ray images using modified VGG19 CNN architecture and YOLO algorithm

doi: 10.1007/s00521-022-06918-x

Figure Lengend Snippet: Comparison of the recommended VGGCOV19-NET COVID-19 diagnosis method with other CNN methods developed using radiology images

Article Snippet: Khan et al. [ ] classified three classes with a new Xception CNN architecture-based CNN model with an accuracy ratio of 95%, Ahammed et al. [ ] classified three classes with the deep CNN model they created with accuracy of 94%, Apostolopoulos and Mpesiana [ ] classified three classes with the pre-trained VGG19 architecture with accuracy of 93.48%, Aslan et al. [ ] classified three classes with the hybrid CNN architecture with accuracy of 98.70%, Hira et al. [ ] classified three classes with the specially ResNeXt-50 with accuracy of 97.55%, and Wang et al. [ ] classified three classes with the deep CNN model they called COVID-Net with an accuracy of 93.3%.

Techniques: Comparison, Biomarker Discovery, Modification, Imaging

Comparison between this work and previous studies.

Journal: Scientific Reports

Article Title: Hybrid of DSR-GAN and CNN for Alzheimer disease detection based on MRI images

doi: 10.1038/s41598-025-94677-9

Figure Lengend Snippet: Comparison between this work and previous studies.

Article Snippet: , CNN-based model (DEMNET) , Kaggle, ADNI datasets , High performance in classifying AD stages , Accuracy: 95.23%, AUC: 97%, Kappa: 0.93 , Class imbalance handled via SMOTE , Lower performance on larger datasets , Robustness testing on ADNI.

Techniques: Comparison, Extraction, Imaging, Biomarker Discovery

Journal: Cell Reports Medicine

Article Title: Integration of deep learning-based histopathology and transcriptomics reveals key genes associated with fibrogenesis in patients with advanced NASH

doi: 10.1016/j.xcrm.2023.101016

Figure Lengend Snippet:

Article Snippet: CNN-based models for quantification of NASH histological features from H&E or Trichrome stained biopsies , PathAI , N/A.

Techniques: Software, Staining

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: