project

BAOS-CNN: A novel deep neuroevolution algorithm for multispecies seagrass detection


Provided by   Edith Cowan University

Research Project

Researchers: Edith Cowan University (Managed by) ,  Jumana Abu-Khalaf (Associated with) ,  Md Noman (Associated with) ,  Paul Lavery (Associated with) ,  Seyed Jalali (Associated with)
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Full description

We developed a novel Deep Neuroevolutionary (DNE) model that can automate the architectural engineering and hyperparameter tuning of CNNs models by developing and using a novel metaheuristic algorithm, named 'Boosted Atomic Orbital Search (BAOS)'. This proposed BAOS-CNN model achieves the highest overall accuracy (97.48%) among the seven evolutionary-based CNN models. The proposed model was tested and evaluated on this multi-species seagrass dataset.

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