2006
DOI: 10.3923/itj.2007.142.147
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Robust Face Detection using Genetic Algorithm

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Cited by 6 publications
(6 citation statements)
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“…In this part, we review soft computing methods that employ evolutionary algorithms for face detection [32][33][34][35][36].…”
Section: Soft Methods For Face Detectionmentioning
confidence: 99%
See 1 more Smart Citation
“…In this part, we review soft computing methods that employ evolutionary algorithms for face detection [32][33][34][35][36].…”
Section: Soft Methods For Face Detectionmentioning
confidence: 99%
“…Early works using genetic algorithm (GA) [32,33] for face detection have included some heuristic techniques for image enhancement such as size normalization, noise filtering, histogram equalization, or gray-scale conversion. In [32], the authors applied GA to find the faces of a given image by using a face template.…”
Section: Soft Methods For Face Detectionmentioning
confidence: 99%
“…Then the set (called a population) of possible solutions (called chromosomes) are generated [21] . A function assigns a degree of fitness to each chromosome in every generation in order to use the best individual during the evolutionary process [20] . In accordance to the objective, the fitness function evaluates the individuals [18] .…”
Section: Related Workmentioning
confidence: 99%
“…Consequently, the partial features of two chromosomes are combined to generate two off springs. The chromosome cloning takes place when a pair of chromosomes does not cross over, thus creating off springs that are exact copies of each parent [20] . The ultimate step in each generation is the mutation of individuals through the alteration of parts of their genes [18] .…”
Section: Related Workmentioning
confidence: 99%
See 1 more Smart Citation