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@article{156174,
        author = {M.Nivetha and Kavin S and Chandru Pandi B and Yogeshwaran. D},
        title = {Brain Tumor Detection Using Convolutional Neural Network in Mobile Devices},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {9},
        number = {2},
        pages = {122-125},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=156174},
        abstract = {Aiming at solving the problem of low accuracy in traditional brain tumor detection and increasing the accessibility of detection techniques to people. The automatic brain tumor classification is an incredibly challenging task in large spatial and structural variability of surrounding region of brain tumor. In this work, automatic brain tumor detection is proposed by using Convolutional Neural Networks (CNN) classification. The deeper architecture design is performed by using small kernels. The weight of the neuron is given as small. Experimental results show that the CNN archives rate of 88.7% accuracy with low complexity and compared with the all- other state of arts methods. And about integrating models with mobile devices in order increase usability and to provide a better experience through offline support for detection},
        keywords = {},
        month = {},
        }