A novel algorithm for identifying the optimal CNN Architectures regulated by Swarm Intelligence
| Autor: | Mangalraj, Mohit Pandya, Sayonee Dassani |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2022 |
| Předmět: | |
| Zdroj: | Intelligent Systems with Applications, Vol 16, Iss , Pp 200145- (2022) |
| Druh dokumentu: | article |
| ISSN: | 2667-3053 88331164 |
| DOI: | 10.1016/j.iswa.2022.200145 |
| Popis: | The Emergence of deep learning architectures in recent years paves a pathway for developing several real-time applications. Deep learning architecture selection is time-consuming since it takes hours to get trained, few architectures take days to get training. To address the pitfall in selecting the architectures, we developed a novel algorithm that returns an optimal architecture to the user with the help of swarm intelligence. The parameters required to run the algorithm have been obtained dynamically from the input samples, so the returned architecture is reliable. The algorithm is tested based on qualitative metrics such as training accuracy and testing accuracy, and the algorithm is evaluated based on quantitative metrics such as convergence time and execution time. The algorithm is robust against any dataset, and the architecture generated by the algorithm yields better results. |
| Databáze: | Directory of Open Access Journals |
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