Learning architecture for brain tumor classification based on deep convolutional neural network: Classic and ResNet50

Learning architecture for brain tumor classification based on deep convolutional neural network: Classic and ResNet50

Accurate classification of brain tumors in medical images is vital for effective diagnosis and treatment planning, which improves the patient’s survival rate. In this paper, we investigate the application of Convolutional Neural Networks (CNN) as a powerful tool for enhancing diagnostic accuracy us...

Full description

Saved in:
Bibliographic Details
Main Authors: Doheir, Mohamed A. S., Mohd Yaacob, Noorayisahbe, Ali, Rabei Raad, Alqaryouti, Marwan Harb, Sadeq, Ala Eddin, Iqtait, Musab, Rachmawanto, Eko Hari, Sari, Christy Atika, Yaacob, Siti Salwani
Format: Article
Language:en
Published: Multidisciplinary Digital Publishing Institute (MDPI) 2025
Online Access:http://eprints.utem.edu.my/id/eprint/29344/2/02723070320251026281684.pdf
http://eprints.utem.edu.my/id/eprint/29344/
https://www.mdpi.com/2075-4418/15/5/624
https://doi.org/10.3390/diagnostics15050624
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

http://eprints.utem.edu.my/id/eprint/29344/2/02723070320251026281684.pdf
http://eprints.utem.edu.my/id/eprint/29344/
https://www.mdpi.com/2075-4418/15/5/624
https://doi.org/10.3390/diagnostics15050624

Similar Items