In both grown-ups and juvenile, brain tumors are the tenth most predominant cause of death rate. There are many different sorts of tumors, and each one has extremely slim odds of survival based on texture, location, and shape. The worst outcomes can result from the incorrect categorization. The quantity of CNN's hidden neurons and convolutional layers is tuned in the suggested deep learning classification. The most effective classifier is the one that has a high rank. Since artificial intelligence techniques have become more prevalent, it is now possible to detect brain cancers by using machine learning and deep learning techniques and algorithms. In order to create an intensive perception, this work extricates various deep features from deep learning models and bolsters them as input to the Adadelta and SGD optimizer. The incredible execution capability of the proposed model is realised utilizing the Adadelta optimizer.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Brain Tumor Detection using VGG19 model on Adadelta and SGD Optimizer


    Contributors:


    Publication date :

    2022-12-01


    Size :

    522492 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Detecting anomalous road traffic conditions using VGG19 CNN Model

    Rajeshwari M. / MallikarjunaRao CH. | DOAJ | 2021

    Free access

    VGG19-based Transfer learning for Rice Plant Illness Detection

    Meena, Rakesh / Joshi, Sunil / Raghuwanshi, Sandeep | IEEE | 2022



    Shipping label generation based on VGG19 network

    Wang, Haifeng / Wu, Tong / Yang, Kun et al. | SPIE | 2023


    BRAKE PERFORMANCE OPTIMIZER

    BRANDIN MAGNUS / EKHOLM DAVID | European Patent Office | 2021

    Free access