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resnet50 model  (Carl Zeiss)


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    Carl Zeiss resnet50 model
    Resnet50 Model, supplied by Carl Zeiss, 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/resnet50+model/model+resnet50/pmc11482640-186-7-17
    Average 90 stars, based on 1 article reviews
    resnet50 model - by Bioz Stars, 2026-09
    90/100 stars

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    other:

    Article Title: Automated Identification of Clinically Relevant Regions in Glaucoma OCT Reports Using Expert Eye Tracking Data and Deep Learning
    Article Snippet: The first two rows of indicate the ResNet50 model performed better on Topcon reports alone than on Zeiss reports alone, in terms of recall, and accuracy.



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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