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efficientnetb3  (Kaggle Inc)
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Kaggle Inc efficientnetb3
Proposed deep visual detection system using <t>EfficientNetB3</t> for binary classification on the Kaggle OSCC dataset.
Efficientnetb3, supplied by Kaggle Inc, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/efficientnetb3/product/Kaggle Inc
Average 86 stars, based on 1 article reviews
efficientnetb3 - by Bioz Stars, 2026-05
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efficientnetb3 architecture  (IEEE Access)
90
IEEE Access efficientnetb3 architecture
Proposed deep visual detection system using <t>EfficientNetB3</t> for binary classification on the Kaggle OSCC dataset.
Efficientnetb3 Architecture, 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/result/efficientnetb3 architecture/product/IEEE Access
Average 90 stars, based on 1 article reviews
efficientnetb3 architecture - by Bioz Stars, 2026-05
90/100 stars
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Image Search Results


Proposed deep visual detection system using EfficientNetB3 for binary classification on the Kaggle OSCC dataset.

Journal: Scientific Reports

Article Title: Deep visual detection system for oral squamous cell carcinoma

doi: 10.1038/s41598-025-34332-5

Figure Lengend Snippet: Proposed deep visual detection system using EfficientNetB3 for binary classification on the Kaggle OSCC dataset.

Article Snippet: This section provides a detailed comparative evaluation of EfficientNetB3, DenseNet121, and ResNet50, analyzing their performance on binary and multi-class OSCC classification using the Kaggle and NDB-UFES datasets presented in Table .

Techniques:

Proposed deep visual detection system using EfficientNetB3 for Multiclass Classification on the NDB-UFES OSCC dataset.

Journal: Scientific Reports

Article Title: Deep visual detection system for oral squamous cell carcinoma

doi: 10.1038/s41598-025-34332-5

Figure Lengend Snippet: Proposed deep visual detection system using EfficientNetB3 for Multiclass Classification on the NDB-UFES OSCC dataset.

Article Snippet: This section provides a detailed comparative evaluation of EfficientNetB3, DenseNet121, and ResNet50, analyzing their performance on binary and multi-class OSCC classification using the Kaggle and NDB-UFES datasets presented in Table .

Techniques:

Proposed deep visual detection system using EfficientNetB3 for multiclass classification on the NDB-UFES OSCC dataset.

Journal: Scientific Reports

Article Title: Deep visual detection system for oral squamous cell carcinoma

doi: 10.1038/s41598-025-34332-5

Figure Lengend Snippet: Proposed deep visual detection system using EfficientNetB3 for multiclass classification on the NDB-UFES OSCC dataset.

Article Snippet: This section provides a detailed comparative evaluation of EfficientNetB3, DenseNet121, and ResNet50, analyzing their performance on binary and multi-class OSCC classification using the Kaggle and NDB-UFES datasets presented in Table .

Techniques:

Key hyperparameters of the EfficientNetB3 model (Kaggle binary class OSCC dataset).

Journal: Scientific Reports

Article Title: Deep visual detection system for oral squamous cell carcinoma

doi: 10.1038/s41598-025-34332-5

Figure Lengend Snippet: Key hyperparameters of the EfficientNetB3 model (Kaggle binary class OSCC dataset).

Article Snippet: This section provides a detailed comparative evaluation of EfficientNetB3, DenseNet121, and ResNet50, analyzing their performance on binary and multi-class OSCC classification using the Kaggle and NDB-UFES datasets presented in Table .

Techniques:

Key hyperparameters of the EfficientNetB3 model (NDB-UFES multiclass OSCC dataset).

Journal: Scientific Reports

Article Title: Deep visual detection system for oral squamous cell carcinoma

doi: 10.1038/s41598-025-34332-5

Figure Lengend Snippet: Key hyperparameters of the EfficientNetB3 model (NDB-UFES multiclass OSCC dataset).

Article Snippet: This section provides a detailed comparative evaluation of EfficientNetB3, DenseNet121, and ResNet50, analyzing their performance on binary and multi-class OSCC classification using the Kaggle and NDB-UFES datasets presented in Table .

Techniques:

Training and validation loss & accuracy curve—EfficientNetB3 (Epochs = 10, Batch Size = 64) Kaggle Binary Class OSCC Dataset.

Journal: Scientific Reports

Article Title: Deep visual detection system for oral squamous cell carcinoma

doi: 10.1038/s41598-025-34332-5

Figure Lengend Snippet: Training and validation loss & accuracy curve—EfficientNetB3 (Epochs = 10, Batch Size = 64) Kaggle Binary Class OSCC Dataset.

Article Snippet: This section provides a detailed comparative evaluation of EfficientNetB3, DenseNet121, and ResNet50, analyzing their performance on binary and multi-class OSCC classification using the Kaggle and NDB-UFES datasets presented in Table .

Techniques: Biomarker Discovery

Training and validation loss & accuracy curve—EfficientNetB3 (Epochs = 20, Batch Size = 32) NDB-UFES Multiclass OSCC Dataset.

Journal: Scientific Reports

Article Title: Deep visual detection system for oral squamous cell carcinoma

doi: 10.1038/s41598-025-34332-5

Figure Lengend Snippet: Training and validation loss & accuracy curve—EfficientNetB3 (Epochs = 20, Batch Size = 32) NDB-UFES Multiclass OSCC Dataset.

Article Snippet: This section provides a detailed comparative evaluation of EfficientNetB3, DenseNet121, and ResNet50, analyzing their performance on binary and multi-class OSCC classification using the Kaggle and NDB-UFES datasets presented in Table .

Techniques: Biomarker Discovery

Confusion matrix of EfficientNetB3 model (Epochs = 10, Batch Size = 64)—Kaggle Binary Class OSCC dataset.

Journal: Scientific Reports

Article Title: Deep visual detection system for oral squamous cell carcinoma

doi: 10.1038/s41598-025-34332-5

Figure Lengend Snippet: Confusion matrix of EfficientNetB3 model (Epochs = 10, Batch Size = 64)—Kaggle Binary Class OSCC dataset.

Article Snippet: This section provides a detailed comparative evaluation of EfficientNetB3, DenseNet121, and ResNet50, analyzing their performance on binary and multi-class OSCC classification using the Kaggle and NDB-UFES datasets presented in Table .

Techniques:

Confusion matrix of EfficientNetB3 model (Epochs = 20, Batch Size = 32)—NDB-UFES multiclass OSCC dataset.

Journal: Scientific Reports

Article Title: Deep visual detection system for oral squamous cell carcinoma

doi: 10.1038/s41598-025-34332-5

Figure Lengend Snippet: Confusion matrix of EfficientNetB3 model (Epochs = 20, Batch Size = 32)—NDB-UFES multiclass OSCC dataset.

Article Snippet: This section provides a detailed comparative evaluation of EfficientNetB3, DenseNet121, and ResNet50, analyzing their performance on binary and multi-class OSCC classification using the Kaggle and NDB-UFES datasets presented in Table .

Techniques:

Performance comparison of EfficientNetB3, DenseNet121, and ResNet50 on Kaggle Binary-Class and NDB-UFES multiclass OSCC datasets.

Journal: Scientific Reports

Article Title: Deep visual detection system for oral squamous cell carcinoma

doi: 10.1038/s41598-025-34332-5

Figure Lengend Snippet: Performance comparison of EfficientNetB3, DenseNet121, and ResNet50 on Kaggle Binary-Class and NDB-UFES multiclass OSCC datasets.

Article Snippet: This section provides a detailed comparative evaluation of EfficientNetB3, DenseNet121, and ResNet50, analyzing their performance on binary and multi-class OSCC classification using the Kaggle and NDB-UFES datasets presented in Table .

Techniques: Comparison