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@article{151640,
        author = {NANDHINIDEVI S and HARISH S and NARRESH M and YOKESHWARAN D},
        title = {Multi classification of brain tumor  MRI images using Deep learning technique},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {8},
        number = {1},
        pages = {439-442},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=151640},
        abstract = {Brain tumor is one of the most dangerous cancers in the world. Adults and children are affected by this cancer. The identification of the correct type at early stage  gives a life to the patient by giving precise treatment. The misclassification of the tumor brain leads to dreadful consequences. By investigating the magnetic resonance imaging (MRI) images of the patient’s brain , physician distinguish the type of brain tumors. The manual examination sometimes leads to misclassification due to various type of tumor and human error. To assist radiologists we proposed a CNN model for multi class classification to identify  the type of tumor such as Glioma tumor, Meninglimoa tumor , Pituitary tumor and No tumor. The proposed  model achieved 93.72 % testing accuracy  and 96.51 validation accuracy.},
        keywords = {},
        month = {},
        }