A GPU-based Evolution Strategy for Optic Disk Detection in Retinal Images
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Published:
2016-07-14
Keywords:
Compute Unified Device Architecture, optic disk, evolutionary strategy, retinal images
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Abstract
Parallel processing using graphic processing units (GPUs) has attracted much research interest in recent years. Parallel computation can be applied to evolution strategy (ES) for processing individuals in a population, but evolutionary strategies are time consuming to solve large computational problems or complex fitness functions. In this paper we describe the implementation of an improved ES for optic disk detection in retinal images using the Compute Unified Device Architecture (CUDA) environment. In the experimental results we show that the computational time for optic disk detection task has a speedup factor of 5x and 7x compared to an implementation on a mainstream CPU.
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How to Cite
Sánchez-Torres, G., & González-Calederón, G. (2016). A GPU-based Evolution Strategy for Optic Disk Detection in Retinal Images. Revista Ingenierías Universidad De Medellín, 15(29), 173-190. https://doi.org/10.22395/rium.v15n29a11