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inception v3  (MathWorks Inc)


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    MathWorks Inc inception v3
    Inception V3, 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/inception-v3/pmc11906377-78-26-32
    Average 90 stars, based on 1 article reviews
    inception v3 - by Bioz Stars, 2026-10
    90/100 stars

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

    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: Feasibility study to improve deep learning in OCT diagnosis of rare retinal diseases with few-shot classification
    Article Snippet: We used Inception-v3 as identical subnetworks for the classes, and the Siamese network was designed as described in the MATLAB 2020b (MathWorks Inc., Natick, MA, USA) example (Fig. ).

    Article Title: Topical Henna Application Causing Acute Kidney Injury and Acute Hemolytic Anemia.
    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.



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    Overview of existing techniques for brain tumor detection.

    Journal: Scientific Reports

    Article Title: Automatic smart brain tumor classification and prediction system using deep learning

    doi: 10.1038/s41598-025-95803-3

    Figure Lengend Snippet: Overview of existing techniques for brain tumor detection.

    Article Snippet: , 2021 , Public (Kaggle) , 253 MRI images , Tumor and No Tumor , 2 , CNN VGG-16 ResNet-50 Inception-V3 , 100% 96% 89% 75%.

    Techniques: Extraction, Biomarker Discovery, Modification