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explainable resnet50 model  (Kaggle Inc)

 
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    Kaggle Inc explainable resnet50 model
    Explainable Resnet50 Model, 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/product/resnet50+model/resnet50/pmc12873157-8-3-13
    Average 86 stars, based on 1 article reviews
    explainable resnet50 model - by Bioz Stars, 2026-11
    86/100 stars

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    Related Articles

    Modification:

    Article Title: A Hybrid Technique for Diabetic Retinopathy Detection Based on Ensemble-Optimized CNN and Texture Features.
    Article Snippet: .. In this research, we designed a deep learning model named GraphNet124 and utilized a modified version of the ResNet50 model for feature extraction from Kaggle EyePACS [21], which is a publicly available dataset. ..

    Extraction:

    Article Title: A Hybrid Technique for Diabetic Retinopathy Detection Based on Ensemble-Optimized CNN and Texture Features.
    Article Snippet: .. In this research, we designed a deep learning model named GraphNet124 and utilized a modified version of the ResNet50 model for feature extraction from Kaggle EyePACS [21], which is a publicly available dataset. ..

    other:

    Article Title: A model for skin cancer using combination of ensemble learning and deep learning
    Article Snippet: Kumar K et al. [ ] developed an advanced skin cancer classification and prediction technique using augmented intelligence with the ResNet50 model on Kaggle datasets.

    Article Title: Deep visual detection system for oral squamous cell carcinoma
    Article Snippet: Fig. 29 Confusion matrix of ResNet50 Model (Epochs = 10, Batch Size = 64) — Kaggle Binary Class OSCC dataset.



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    Image Search Results


    Proposed deep visual detection system using ResNet50 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 ResNet50 for binary classification on the Kaggle OSCC dataset.

    Article Snippet: Fig. 25 Key Hyperparameters of the ResNet50 model (Kaggle Binary Class OSCC Dataset).

    Techniques:

    Proposed deep visual detection system using ResNet50 for multiclass 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 ResNet50 for multiclass classification on the Kaggle OSCC dataset.

    Article Snippet: Fig. 25 Key Hyperparameters of the ResNet50 model (Kaggle Binary Class OSCC Dataset).

    Techniques:

    Key Hyperparameters of the ResNet50 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 ResNet50 model (Kaggle Binary Class OSCC Dataset).

    Article Snippet: Fig. 25 Key Hyperparameters of the ResNet50 model (Kaggle Binary Class OSCC Dataset).

    Techniques:

    Key Hyperparameters of the ResNet50 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 ResNet50 model (NDB-UFES Multiclass OSCC Dataset).

    Article Snippet: Fig. 25 Key Hyperparameters of the ResNet50 model (Kaggle Binary Class OSCC Dataset).

    Techniques:

    Training and validation loss & accuracy curve—ResNet50 (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—ResNet50 (Epochs = 10, Batch Size = 64) Kaggle binary class OSCC Dataset.

    Article Snippet: Fig. 25 Key Hyperparameters of the ResNet50 model (Kaggle Binary Class OSCC Dataset).

    Techniques: Biomarker Discovery

    Training and validation loss & accuracy curve—ResNet50 (Epochs = 20, Batch Size = 64) 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—ResNet50 (Epochs = 20, Batch Size = 64) NDB-UFES multiclass OSCC dataset.

    Article Snippet: Fig. 25 Key Hyperparameters of the ResNet50 model (Kaggle Binary Class OSCC Dataset).

    Techniques: Biomarker Discovery

    Confusion matrix of ResNet50 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 ResNet50 Model (Epochs = 10, Batch Size = 64) — Kaggle Binary Class OSCC dataset.

    Article Snippet: Fig. 25 Key Hyperparameters of the ResNet50 model (Kaggle Binary Class OSCC Dataset).

    Techniques:

    Confusion matrix of ResNet50 Model (Epochs = 20, Batch Size = 64) — 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 ResNet50 Model (Epochs = 20, Batch Size = 64) — NDB-UFES Multiclass OSCC dataset.

    Article Snippet: Fig. 25 Key Hyperparameters of the ResNet50 model (Kaggle Binary Class OSCC Dataset).

    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: Fig. 25 Key Hyperparameters of the ResNet50 model (Kaggle Binary Class OSCC Dataset).

    Techniques: Comparison