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resnet50  (MathWorks Inc)


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    MathWorks Inc resnet50
    Resnet50, supplied by MathWorks Inc, 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/resnet50/product/MathWorks Inc
    Average 90 stars, based on 1 article reviews
    resnet50 - by Bioz Stars, 2026-03
    90/100 stars

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    Image Search Results


    Unified reference model showing the integration of handcrafted EAR/MAR-based behavioral cues with the dual-stream CNN architecture (EfficientNetB0 + ResNet50) in the proposed EffRes-DrowsyNet framework.

    Journal: Sensors (Basel, Switzerland)

    Article Title: EffRes-DrowsyNet: A Novel Hybrid Deep Learning Model Combining EfficientNetB0 and ResNet50 for Driver Drowsiness Detection

    doi: 10.3390/s25123711

    Figure Lengend Snippet: Unified reference model showing the integration of handcrafted EAR/MAR-based behavioral cues with the dual-stream CNN architecture (EfficientNetB0 + ResNet50) in the proposed EffRes-DrowsyNet framework.

    Article Snippet: [ ] , 2024 , Face for signs of tiredness , ResNet50 , Model trained on Kaggle dataset, test accuracy achieved at epoch 20 , 95.02%, Loss: 0.1349 , Kaggle (Varied Dataset).

    Techniques:

    The first row is the original raw image. The second row is the class activation mapping plus plus (CAM++) of the ResNet50. The third row is the fined-grained lesion detection visualization from the proposed FKD-CSS model. FKD fine-grained knowledge distillation. CSS corneal staining score.

    Journal: NPJ Digital Medicine

    Article Title: Advanced and interpretable corneal staining assessment through fine grained knowledge distillation

    doi: 10.1038/s41746-025-01706-y

    Figure Lengend Snippet: The first row is the original raw image. The second row is the class activation mapping plus plus (CAM++) of the ResNet50. The third row is the fined-grained lesion detection visualization from the proposed FKD-CSS model. FKD fine-grained knowledge distillation. CSS corneal staining score.

    Article Snippet: We trained a U-Net on the SUSTech-SYSU dataset utilizing a pre-trained ResNet50 backbone on ImageNet for automatic corneal segmentation.

    Techniques: Activation Assay, Distillation, Staining