DB-FGA-Net fuses VGG16 and Xception backbones with a new Frequency-Gated Attention module to reach 99.24% accuracy on 4-class brain tumor classification without augmentation and generalizes to 95.77% on an independent dataset.
Hussain Hassan, Wadii Boulila,Efficient Approach for Brain Tumor Detection and Classification Using Fuzzy Thresholding and Deep Learning Algorithms, IEEE Access, vol
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DB-FGA-Net: Dual Backbone Frequency Gated Attention Network for Multi-Class Brain Tumor Classification with Grad-CAM Interpretability
DB-FGA-Net fuses VGG16 and Xception backbones with a new Frequency-Gated Attention module to reach 99.24% accuracy on 4-class brain tumor classification without augmentation and generalizes to 95.77% on an independent dataset.