Optimization of Deep Neural Networks Using a Micro Genetic Algorithm

This work proposes the use of a micro genetic algorithm to optimize the architecture of fully connected layers in convolutional neural networks, with the aim of reducing model complexity without sacrificing performance. Our approach applies the paradigm of transfer learning, enabling training withou...

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Bibliographic Details
Main Authors: Ricardo Landa, David Tovias-Alanis, Gregorio Toscano
Format: Article
Language:English
Published: MDPI AG 2024-12-01
Series:AI
Subjects:
Online Access:https://www.mdpi.com/2673-2688/5/4/127
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