26224ab4184a136f282-4294 20230107080759648 beie:beie director@blueeyesintelligence.org WEB-FORM International Journal of Recent Technology and Engineering (IJRTE) IJRTE 22773878 10.35940/ijrte.2277-3878 https://www.ijrte.org/ 01 30 2023 11 5 Department of Electronics and Telecommunication Engineering, Jabalpur Engineering College, Jabalpur (M.P), India Farha Anjum Mansoori https://orcid.org/0000-0002-3810-7482 Dr. Agya Mishra Department of Electronics and Telecommunication Engineering, Jabalpur Engineering College, Jabalpur (M.P), India. This paper presents an intelligent technique particularly for MRI brain images. This introduces a clever method designed specifically for MRI brain pictures. To determine the abnormality in the brain images is processed using intelligent hybrid method of convolution neural networks and curvelet transform. Feature extraction, the logistic regression method (LRM), and learning algorithms are all used in the proposed model. Additionally, the categorization system identifies cancerous or non-cancerous tumours in the images of the brain. Results from experiments demonstrate how well model- and parameter-based analysis performs. The topic of minimum batch accuracy and validation accuracy, which are then contrasted with the current method, comes to a conclusion in the paper. This concept is suited to ongoing MRI image analysis activities. In this paper, previous paper has also be reviewed and their method is investigated. 01 30 2023 77 85 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true Not receive. No conflicts of interest to the best of our knowledge. No, the article does not require ethical approval and consent to participate with evidence. Not relevant. All authors have equal participation in this article. 10.35940/ijrte.E7433.0111523 https://www.ijrte.org/portfolio-item/e74330111523/