2024
DOI: 10.29304/jqcsm.2024.16.11450
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Optimizing the Architecture of Convolutional Neural Networks Using Modified Salp Swarm Algorithm

Entesar H. Abdulsaed,
Maytham Alabbas,
Raidah S. Khudeyer

Abstract: Deep learning is highly effective in dealing with complex tasks such as image classification and recognition. However, finding the optimal architecture's hyperparameters for Convolutional Neural Networks (CNNs) to achieve the best performance and parameter regularization can be challenging. Metaheuristic optimization algorithms can be utilized to find solutions in this context. In this research, a computerized CNN was adjusted using an improved Salp Swarm Algorithm (SSA) to enhance crucial CNN settings, like d… Show more

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References 42 publications
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