Metaheuristic Algorithms and Optimizing Neural Networks for Biomedical Image Processing
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Metaheuristic Algorithms and Optimizing Neural Networks for Biomedical Image Processing

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Metaheuristic algorithms emerge as powerful tools for optimizing complex systems, particularly in neural networks, where traditional methods may cause challenges. In biomedical image processing, the integration of metaheuristics like genetic algorithms, particle swarm optimization, and differential evolution offers promising improvements in neural network performance. These algorithms help improve hyperparameters and optimize architectures, enhancing the accuracy of tasks like disease detection, image segmentation, and classification. Further research into this convergence between metaheuristi...