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Bio-medical image processing is a challenging and most emerging field in the computer based medical diagnosis. Brain tumors are most common and harmful disease these days, over a thousands people suffering annually with brain tumors. Among different types of brain tumors Gliomas are most common (around 30% of all brain tumor). Magnetic Resonance imaging (MRI) is a well received imaging approach to identify brain tumors. The classification of brain MRI is a difficult task. Due to large number of MRI images manual analysis is tedious and pron to errors. So there is a need of automatic classification method. The proposed method focus on a binary classification problem that seeks to differentiate between normal and tumorous MRI images by using the idea of deep transfer learning with the help of a pre-trained VGG16 model. The proposed method achieve an accuracy of 91.8% and consume less …