Titlebook: Evolutionary Computation Techniques: A Comparative Perspective; Erik Cuevas,Valentín Osuna,Diego Oliva Book 2017 Springer International Pu

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https://doi.org/10.1007/978-3-658-26484-0n exhaustive computation of SAD values for all elements of the search window. However, several fast BM algorithms have been lately presented to reduce the number of SAD operations by calculating only a fixed subset of search locations at the price of poor accuracy. In this chapter, a new algorithm b

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S. Weissman Dr. phil., Dipl. Psychologinl problems. This chapter describes the use of the Artificial Bee Colony (ABC) algorithm to accurately identify the solar cells’ parameters. The ABC algorithm is an evolutionary method inspired by the intelligent foraging behavior of honeybees. In comparison with other evolutionary algorithms, ABC ex

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Multi-circle Detection on Images,evolved through the Artificial Bee Colony (ABC) algorithm so the best candidate (global optimum) can be fitted into an actual circle within the edge-only image. An analysis of the incorporated exhausted-sources memory is executed in order to identify potential local optima i.e. other circles. The ov

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Template Matching, new bio-inspired algorithms have emerged with applications for detection, optimization and classification for its use in image processing. In this chapter, the Social Spider Optimization (SSO) algorithm is presented to reduce the number of search locations in the TM process. The SSO algorithm is ba

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Motion Estimation,n exhaustive computation of SAD values for all elements of the search window. However, several fast BM algorithms have been lately presented to reduce the number of SAD operations by calculating only a fixed subset of search locations at the price of poor accuracy. In this chapter, a new algorithm b

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