Publicação: Fine-tuning deep belief networks using cuckoo search
Carregando...
Data
Autores
Orientador
Coorientador
Pós-graduação
Curso de graduação
Título da Revista
ISSN da Revista
Título de Volume
Editor
Tipo
Capítulo de livro
Direito de acesso
Resumo
In the last few years, metaheuristic-driven optimization has been employed to address deep belief network (DBN) model selection, since it provides simple and elegant solutions in a wide range of applications. In this work, we introduce the well-known cuckoo search to fine-tune DBN parameters and validate its effectiveness by comparing it with harmony search, improved harmony search, and particle swarm optimization. The experimental results have been carried out in two public datasets using DBNs with a different number of layers concerning the task of binary image reconstruction.
Descrição
Palavras-chave
Cuckoo search, Deep belief networks, Harmony search, Metaheuristic, Model selection, Particle swarm optimization
Idioma
Inglês
Como citar
Bio-Inspired Computation and Applications in Image Processing, p. 47-59.
