Fine-tuning deep belief networks using cuckoo search
Nenhuma Miniatura disponível
Data
2016-08-11
Autores
Rodrigues, D.
Yang, X. S.
Papa, J. P. [UNESP]
Título da Revista
ISSN da Revista
Título de Volume
Editor
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
Como citar
Bio-Inspired Computation and Applications in Image Processing, p. 47-59.