Recursive Neural Networks Based on PSO for Image Parsing
This paper presents an image parsing algorithm which is based on Particle Swarm Optimization (PSO) and Recursive Neural Networks (RNNs). State-of-the-art method such as traditional RNN-based parsing strategy uses L-BFGS over the complete data for learning the parameters. However, this could cause pr...
Main Authors: | Guo-Rong Cai, Shui-Li Chen |
---|---|
Format: | Article |
Language: | English |
Published: |
Hindawi Limited
2013-01-01
|
Series: | Abstract and Applied Analysis |
Online Access: | http://dx.doi.org/10.1155/2013/617618 |
Similar Items
-
Transition based neural network dependency parsing of Tibetan
by: Duo Jiecairang, et al.
Published: (2021-01-01) -
Fragment-based Recursive Auto-associative Memory Parsing with Semantic Clues
by: Zhou, Cong-Yan, et al.
Published: (2015) -
Transition-Based Dependency Parsing with Neural Networks
by: Gylling, Joakim
Published: (2017) -
Sentence Compression by Removing Recursive Structure from Parse Tree
by: Matsubara, Shigeki, et al.
Published: (2008) -
Image Resteoration by BP Neural Based on PSO
Published: (2018-08-01)