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What is Explainable Deep Learning for Brain Tumor Detection about?

This study presents an explainable ensemble deep learning model utilizing transfer learning from DenseNet121 and InceptionV3 for the detection and classification of brain tumors, specifically meningioma, glioma, and pituitary tumors. The model achieved high accuracy rates, including 99.02% accuracy and 98.86% F1 score, while employing gradient-weighted class activation maps (Grad-CAM) to enhance interpretability of results. The proposed approach outperformed existing methods and was validated on a publicly

Author

sht2874510

Language

EN