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alsadhan 2025 vgg16 resnet50  (Kaggle Inc)

 
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    Kaggle Inc alsadhan 2025 vgg16 resnet50
    Alsadhan 2025 Vgg16 Resnet50, 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/resnet50/pm42250854-449-1-6
    Average 86 stars, based on 1 article reviews
    alsadhan 2025 vgg16 resnet50 - by Bioz Stars, 2026-09
    86/100 stars

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    Related Articles

    other:

    Article Title: A Robust ConvNeXt-Based Framework for Efficient, Generalizable, and Explainable Brain Tumor Classification on MRI
    Article Snippet: Shanto et al. [ ] , Kaggle dataset , 7023 , 4 , ResNet50, Transformer encoder , Hybrid CNN-Transformer , 99.00 , 100 , 100 , 99.00 , - , - , Grad-CAM , X , X , X , X.

    Article Title: Deep visual detection system for oral squamous cell carcinoma
    Article Snippet: ResNet50 was evaluated on both the Kaggle (binary) and NDB-UFES (multi-class) datasets using varied training configurations.

    Article Title: Brain tumor classification using optimized ResNet50 with dynamic precision optimization for enhanced speed and diagnostic accuracy
    Article Snippet: , 2023 , Multi Classification , Kaggle , ResNet50 , 92.

    Modification:

    Article Title: BrainView: A cloud-based deep learning system for brain image segmentation, tumor detection and visualization
    Article Snippet: .. [ ] , 2023 , Modified ResNet50 with HOG , Kaggle , 88 , 80 , – , –. ..



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    Fine KNN confusion matrix (A) for ResNet50 and (B) for InceptionNetv3 model.

    Journal: International Dental Journal

    Article Title: Dual Framework for Classification and Detection of Third Molar Impaction in Panoramic Radiographs

    doi: 10.1016/j.identj.2026.109430

    Figure Lengend Snippet: Fine KNN confusion matrix (A) for ResNet50 and (B) for InceptionNetv3 model.

    Article Snippet: The deep feature extraction and classification pipelines employing ResNet50 and InceptionNetV3 were executed on the Kaggle platform, leveraging an NVIDIA P100 GPU.

    Techniques: