Fast image representation with GPU-based growing neural gas

Garcia Rodriguez, Jose, Angelopoulou, Anastassia, Morrell, Vicente, Orts, Sergio, Psarrou, Alexandra and García-Chamizo, Juan Manuel (2011) Fast image representation with GPU-based growing neural gas. In: Advances in Computational Intelligence: 11th International Work-Conference on Artificial Neural Networks, IWANN 2011, Torremolinos-Málaga, Spain, June 8-10, 2011, Proceedings, Part II. Lecture notes in computer science (6692). Springer, pp. 58-65. ISBN 9783642214974

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This paper aims to address the ability of self-organizing neural network models to manage real-time applications. Specifically, we introduce a Graphics Processing Unit (GPU) implementation with Compute Unified Device Architecture (CUDA) of the Growing Neural Gas (GNG) network. The Growing Neural Gas network with its attributes of growth, flexibility, rapid adaptation, and excellent quality representation of the input space makes it a suitable model for real time applications. In contrast to existing algorithms the proposed GPU implementation allow the acceleration keeping good quality of representation. Comparative experiments using iterative, parallel and hybrid implementation are carried out to demonstrate the effectiveness of CUDA implementation in representing linear and non-linear input spaces under time restrictions.

Item Type: Book Section
Subjects: University of Westminster > Science and Technology > Electronics and Computer Science, School of (No longer in use)
Depositing User: Miss Nina Watts
Date Deposited: 15 Sep 2011 11:53
Last Modified: 15 Sep 2011 11:59

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