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Glioma is a kind of brain tumor that can arise at a distinct location along with dissimilar appearance and size. The high-grade glioma (HGG) is a serious kind of cancer when compare to low-graded glioma (LGG). The manual diagnosis process of these tumors is tiring and time consuming. Therefore, in clinical practices, MRI is useful to assess gliomas as it provides essential information of tumor regions. In this manuscript, an active deep learning-based feature selection approach is suggested to segment and recognize brain tumors. Contrast enhancement is made in the primary step and supplied to SbDL for saliency map construction, which later converts into binarized form by applying simple thresholding. In the classification phase, the Inception V3 pre-trained CNN model is employed for deep feature extraction. These features are simply concatenated along with dominant rotated LBP (DRLBP) for better texture …