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

Autor: Jonathan Fregoso, Claudia I. Gonzalez, Gabriela E. Martinez

Publikováno v: Axioms, Vol 10, Iss 3, p 139 (2021)

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 network

Externí odkaz: https://doaj.org/article/be0060143d3344fca3042f7d93af7613

Parameter Optimization of a Convolutional Neural Network Using Particle Swarm Optimization

Autor: Claudia I. Gonzalez, Gabriela E. Martinez, Jonathan Fregoso

Publikováno v: Fuzzy Logic Hybrid Extensions of Neural and Optimization Algorithms: Theory and Applications ISBN: 9783030687755
Fuzzy Logic Hybrid Extensions of Neural and Optimization Algorithms

In this paper, parameter optimization of Convolutional Neural Network architectures is proposed by applying the Particle Swarm Optimization algorithm, where the parameters that are optimized are: the number of layers, number of convolution filters, t

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::e395af69fea4f5bc9a43fbab9fffec81
https://doi.org/10.1007/978-3-030-68776-2_9