Learning Architecture for Brain Tumor Classification Based on Deep Convolutional Neural Network: Classic and ResNet50

<b>Background:</b> 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 en...

Full description

Saved in:

Bibliographic Details
Main Authors:	Rabei Raad Ali, Noorayisahbe Mohd Yaacob, Marwan Harb Alqaryouti, Ala Eddin Sadeq, Mohamed Doheir, Musab Iqtait, Eko Hari Rachmawanto, Christy Atika Sari, Siti Salwani Yaacob
Format:	Article
Language:	English
Published:	MDPI AG 2025-03-01
Series:	Diagnostics
Subjects:	deep learning Convolutional Neural Networks ResNet-50 image classification magnetic resonance imaging
Online Access:	https://www.mdpi.com/2075-4418/15/5/624
Tags:	Add Tag No Tags, Be the first to tag this record!

Be the first to leave a comment!

Learning Architecture for Brain Tumor Classification Based on Deep Convolutional Neural Network: Classic and ResNet50

Similar Items