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mobilenet-v2  (MathWorks Inc)


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    MathWorks Inc mobilenet-v2
    Mobilenet V2, 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/product/mobilenet-v2/mobilenet+v2/pm39001177-200-15-11
    Average 90 stars, based on 1 article reviews
    mobilenet-v2 - by Bioz Stars, 2026-11
    90/100 stars

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    other:

    Article Title: Predicting the Arousal and Valence Values of Emotional States Using Learned, Predesigned, and Deep Visual Features
    Article Snippet: As mentioned previously, we experimented with two pretrained MATLAB CNNs: ResNet-18 and MobileNet-v2 in [ , ].

    Article Title: 3D shearlet-based descriptors combined with deep features for the classification of Alzheimer's disease based on MRI data.
    Article Snippet: In this study, we propose to use four pretrained CNN models in MATLAB® 2020b that can handle the complexity of MRI datasets: SqueezeNet-v1.1 [49], MobileNet-v2 [50], Xception [51], and Inception-v3 [52].

    Article Title: Predicting the Arousal and Valence Values of Emotional States Using Learned, Predesigned, and Deep Visual Features.
    Article Snippet: Deep Machine Learning As mentioned previously, we experimented with two pretrained MATLAB CNNs: ResNet-18 and MobileNet-v2 in [4,5].



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    Image Search Results


    Various existing models are used in bone fracture detection.

    Journal: Scientific Reports

    Article Title: Exploring the impact of hyperparameter and data augmentation in YOLO V10 for accurate bone fracture detection from X-ray images

    doi: 10.1038/s41598-025-93505-4

    Figure Lengend Snippet: Various existing models are used in bone fracture detection.

    Article Snippet: MobileNet V2 , Bone fracture dataset, Mendeley Data V1. , The model has yielded an accuracy of 93.5% , MobileNet V2 model is a lightweight model, it finds it difficult to capture complex features and subtle details in high-resolution X-ray images.

    Techniques:

    Architecture, optimized hyperparameters and performance of the three final classification models

    Journal: Indian Journal of Ophthalmology

    Article Title: In vivo identification of angle dysgenesis and its relation to genetic markers associated with glaucoma using artificial intelligence

    doi: 10.4103/IJO.IJO_1456_23

    Figure Lengend Snippet: Architecture, optimized hyperparameters and performance of the three final classification models

    Article Snippet: In MATLAB, all the available 19 pretrained convolutional neural network (CNN) models, including SqueezeNet, ResNet-18, GoogleNet, ResNet-50, DarkNet-53, DarkNet-19, ShuffleNet, NasnetMobile, Nasnet Large, Xception, Place-365-Google, MobileNet V2, DenseNet-201, Inception-ResNet V2, Inception-V3, ResNet-101, VGG-19, VGG-16, and AlexNet, were trained using our datasets.

    Techniques: Biomarker Discovery