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A Deep Learning Model Based On Concatenation Approach For The Diagnosis of Brain Tumor PDF

10 Pages·2021·English
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by ['pavithr']| 2021| 10 pages| English

About A Deep Learning Model Based On Concatenation Approach For The Diagnosis of Brain Tumor

This document discusses a deep learning model for brain tumor diagnosis and classification using magnetic resonance imaging (MRI). It proposes extracting multi-level features from pre-trained Inception-v3 and DenseNet201 models and concatenating these features. Two scenarios are evaluated: 1) extracting and concatenating features from Inception modules and classifying tumors, and 2) extracting and concatenating features from DenseNet blocks and classifying tumors. Both approaches achieved over 99% accuracy on a public brain tumor dataset. The proposed multi-level feature extraction and concatenation method outperformed existing deep learning and machine learning methods for brain tumor classification.

Detailed Information

Author:['pavithr']
Publication Year:2021
Pages:10
Language:English
Format:PDF
Price:FREE
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