Abstract
Abstract: In this study, we introduce a method for brain tumor detection that uses CNNs, specifically VGG16 and ResNet50, along with genetic algorithms for model optimization. Integrating advanced deep learning and evolutionary techniques improves the accuracy and efficiency of brain tumor identification in medical images. Experimental results confirm the effectiveness of this method and demonstrate its potential to improve medical diagnosis. In this study, we use genetic algorithms to fine-tune neural network parameters to overcome convergence problems and avoid local minima in high-dimensional spaces. This study promises more accurate and timely identification of brain tumors in medicine by combining AI and medical imaging for future advances. Keywords: CNN, genetic algorithm, VGG16, ResNet50.
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