Recursive Neural Networks Based on PSO for Image Parsing
Joint Authors
Source
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-04-08
Country of Publication
Egypt
No. of Pages
7
Main Subjects
Abstract EN
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 problems due to the nondifferentiable objective function.
In order to solve this problem, the PSO algorithm has been employed to tune the weights of RNN for minimizing the objective.
Experimental results obtained on the Stanford background dataset show that our PSO-based training algorithm outperforms traditional RNN, Pixel CRF, region-based energy, simultaneous MRF, and superpixel MRF.
American Psychological Association (APA)
Cai, Guo-Rong& Chen, Shui-Li. 2013. Recursive Neural Networks Based on PSO for Image Parsing. Abstract and Applied Analysis،Vol. 2013, no. 2013, pp.1-7.
https://search.emarefa.net/detail/BIM-485518
Modern Language Association (MLA)
Cai, Guo-Rong& Chen, Shui-Li. Recursive Neural Networks Based on PSO for Image Parsing. Abstract and Applied Analysis No. 2013 (2013), pp.1-7.
https://search.emarefa.net/detail/BIM-485518
American Medical Association (AMA)
Cai, Guo-Rong& Chen, Shui-Li. Recursive Neural Networks Based on PSO for Image Parsing. Abstract and Applied Analysis. 2013. Vol. 2013, no. 2013, pp.1-7.
https://search.emarefa.net/detail/BIM-485518
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-485518