Enhancing Brain Tumor Classification by a Comprehensive Study on Transfer Learning Techniques and Model Efficiency Using MRI Datasets

Brain tumors, a significant health concern, are a leading cause of mortality globally, with an annual projected increase of 5% by the World Health Organization. This work aims to comprehensively analyze the performance of transfer learning methods in identifying the types of brain tumors, with a par...

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Veröffentlicht in:	IEEE access Jg. 12; S. 100407 - 100418
Hauptverfasser:	Shamshad, Nadia, Sarwr, Danish, Almogren, Ahmad, Saleem, Kiran, Munawar, Alia, Rehman, Ateeq Ur, Bharany, Salil
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	IEEE 2024
Schlagworte:	Accuracy Artificial intelligence Brain modeling Brain tumors CNNs Convolutional neural networks Deep learning deep learning models Feature extraction Machine learning machine learning programming Magnetic resonance imaging Mobile communication MobileNet ResNet-50 Transfer learning Tumors VGG-16
ISSN:	2169-3536, 2169-3536
Online-Zugang:	Volltext
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