Automated Brain Tumor Classification using Fusion Model of VGG19 – EfficientNetB0

Automated Brain Tumor Classification using Fusion Model of VGG19 – EfficientNetB0

Registration ID: IJNRD_216310

Published ID: IJNRD2403665

DOI: Click Here to Get

GEETHA N , Tejashwini P S , Dr. Thriveni J

Fusion, Transfer learning, EfficientNetB0, VGG16.

The increasing mortality rate attributed to brain tumors, characterized by abnormal clusters of rapidly dividing cells in or around the brain, poses a growing concern. Early detection significantly improves survival prospects, underscoring the necessity of tools with automated assistance for prompt diagnosis. Magnetic resonance (MR) images play a crucial role in detecting brain tumors, with various deep learning algorithms like VGG19 and EfficientNetB0 being utilized. To capitalize on the strengths of these algorithms, a Fusion Model is employed, amalgamating their respective capabilities. This fusion model underwent testing on a challenging dataset comprising 7,023 MRI brain tumor images, yielding impressive results. It demonstrated 100% accuracy during training and 99% during testing, highlighting its efficacy in enhancing CNN performance for image classification on the Kaggle dataset Br35H.

Published Paper   E-Certificate

"Automated Brain Tumor Classification using Fusion Model of VGG19 – EfficientNetB0 ", IJNRD - INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (www.IJNRD.org), ISSN:2456-4184, Vol.9, Issue 3, page no.g524-g531, March-2024, Available :https://ijnrd.org/papers/IJNRD2403665.pdf

Volume 9 Issue 3, March-2024

Pages : g524-g531

Paper Reg. ID: IJNRD_216310

Published Paper Id: IJNRD2403665

Downloads: 000121145

Research Area: Computer Science & Technology 

Country: Bengaluru, Karnataka, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2403665.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2403665

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

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

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Publisher: IJNRD (IJ Publication) Janvi Wave

This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition

Call For Paper - Volume 10 | Issue 8 | August 2025

IJNRD is Scholarly open access journals, Peer-reviewed, and Refereed Journals, High Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool), Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI) with Open-Access Publications.

INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (IJNRD) aims to explore advances in research pertaining to applied, theoretical and experimental Technological studies. The goal is to promote scientific information interchange between researchers, developers, engineers, students, and practitioners working in and around the world. IJNRD will provide an opportunity for practitioners and educators of engineering field to exchange research evidence, models of best practice and innovative ideas.

Indexing In Google Scholar, SSRN, ResearcherID-Publons, Semantic Scholar | AI-Powered Research Tool, Microsoft Academic, Academia.edu, arXiv.org, Research Gate, CiteSeerX, ResearcherID Thomson Reuters, Mendeley : reference manager, DocStoc, ISSUU, Scribd, and many more

How to submit the paper?

Important Dates for Current issue

Paper Submission Open For: August 2025

Current Issue: Volume 10 | Issue 8

Last Date for Paper Submission: Till 31-Aug-2025

Notification of Review Result: Within 1-2 Days after Submitting paper.

Publication of Paper: Within 01-02 Days after Submititng documents.

Frequency: Monthly (12 issue Annually).

Journal Type: International Peer-reviewed, Refereed, and Open Access Journal.

Subject Category: Research Area