Brain Tumor Detection using Mobilenet

Registration ID: IJNRD_191759

Published ID: IJNRD2304363

DOI: Click Here to Get

Chede Anusha , P Anil kumar , D Yuva Karthikeswar , G Venkata Sai , B Jaswanth Satya Venkat

CNN, MobileNet, Brain Tumor, Accuracy

ABSTRACT: The research suggests a MobileNet-based CNN-based method for the automatic detection of brain cancers. The suggested approach pre-processes the data using an ImageDataGenerator and trains the model on a bespoke dataset of brain MRI pictures. The trained model is tested against a different testing dataset and exhibits good tumor detection accuracy. The project also offers charts of accuracy and loss over epochs for visualising the model's performance. The suggested method serves as a valuable illustration of how to apply a CNN-based strategy for medical picture analysis as well as a demonstration of the efficacy of deep learning models for the diagnosis of brain cancers.

Published Paper   E-Certificate

Chede Anusha, P Anil kumar, D Yuva Karthikeswar, G Venkata Sai, & B Jaswanth Satya Venkat (April-2023). Brain Tumor Detection using Mobilenet. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 8(4), d443-d448. https://ijnrd.org/papers/IJNRD2304363.pdf

Volume 8 Issue 4, April-2023

Pages : d443-d448

Paper Reg. ID: IJNRD_191759

Published Paper Id: IJNRD2304363

Downloads: 000121975

Research Area: Electronics & Communication Engg. 

Country: Krishna, Andhra Pradesh, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2304363.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2304363

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

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Call For Paper - Volume 10 | Issue 10 | October 2025

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