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Brain Tumor Classification via CNN & MRI by Hà Anh Vũ is a document available to read on EtoBox.

This conference paper presents a hybrid method for classifying brain tumors using MRI images, combining Convolutional Neural Networks (CNN) with supervised machine learning algorithms like K-Nearest Neighbor (KNN), Support Vector Machine (SVM), and Linear Discriminant Analysis (LDA). The study utilizes a dataset of 6,321 MRI images across four tumor classes, achieving an accuracy of 98.40% with the ShuffleNet architecture and SVM classifier. The research highlights the effectiveness of AI and machine learni

Author

Hà Anh Vũ

Language

EN