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model efficientnetb3 binary classification accuracy  (Kaggle Inc)

 
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    Kaggle Inc model efficientnetb3 binary classification accuracy
    Model Efficientnetb3 Binary Classification Accuracy, 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/binary+classification+model/resnet50/pmc13266174-27-50-22
    Average 86 stars, based on 1 article reviews
    model efficientnetb3 binary classification accuracy - by Bioz Stars, 2026-11
    86/100 stars

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    Related Articles

    other:

    Article Title: Deep visual detection system for oral squamous cell carcinoma
    Article Snippet: The Kaggle model (binary classification) showed balanced TP and TN with minimal FP and FN.

    Article Title: Comprehensive benchmarking of deep learning architectures for multiclass histopathological classification of oral epithelial lesions
    Article Snippet: Akram et al. 2026 , Pakistan , Deep Visual Detection System (DVDS); EfficientNetB3; DenseNet121; ResNet50 , DL , 5192 (Normal vs OSCC- Kaggle) 3763 (OSCC, leukoplakia with dysplasia, leukoplakia without dysplasia- NDB-UFES Dataset) , Normal vs OSCC & OSCC vs leukoplakia with dysplasia vs leukoplakia without dysplasia , Best Performing Model (EfficientNetB3) Binary classification- Accuracy: 97.05 Precision: 97.05% Recall (Sensitivity): 96.92% F1-score: 97.05% Multi-class classification- Accuracy: 97.16% Precision: 97.16% Recall: 97.16% F1-score: 97.16%.



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