Optimization of Convolutional Neural Networks Architectures Using PSO for Sign Language Recognition

Optimization of Convolutional Neural Networks Architectures Using PSO for Sign Language Recognition

This paper presents an approach to design convolutional neural network architectures, using the particle swarm optimization algorithm. The adjustment of the hyper-parameters and finding the optimal network architecture of convolutional neural networks represents an important challenge. Network perfo...

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Bibliographic Details
Main Authors: Jonathan Fregoso, Claudia I. Gonzalez, Gabriela E. Martinez
Format: Article
Language:English
Published: MDPI AG 2021-06-01
Series:Axioms
Subjects:
PSO
sign language recognition
optimization of convolutional neural networks
Online Access:https://www.mdpi.com/2075-1680/10/3/139

Internet

https://www.mdpi.com/2075-1680/10/3/139

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