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What is Gravitational Wave Classification with CNNs about?

The project investigates the use of Bayesian Optimization (BO) algorithms to enhance the performance of Convolutional Neural Networks (CNNs) in classifying gravitational waves from background noise. Using a Kaggle dataset, the base model achieved an accuracy of 83.61%, while the BO model improved this slightly to 84.34%, albeit with increased computational resource requirements. The study highlights the trade-off between performance gains and resource efficiency in gravitational wave classification tasks.

Author

Dana S. Hama Amin

Language

EN