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Overview of Actual Approaches to Optimization
Hudecová, Patrícia ; Šůstek, Martin (referee) ; Zbořil, František (advisor)
This work aimed to study some of the optimization algorithms inspired by nature and to test their success in finding the extreme of a function on various functions. Four algorithms were selected, namely the bat algorithm, the firefly algorithm, the flower pollination algorithm, and the black hole algorithm. The Griewank function, the Rastringin function, and the Rosenbrock function were chosen as test functions for finding the extreme of the function. The work contains a description of individual algorithms, a description of test functions and a description of the experiments, and an evaluation of the success of the algorithms.
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Segmentation of optic disc in retinal image data
Juráček, Radek ; Mézl, Martin (referee) ; Odstrčilík, Jan (advisor)
This bachelor thesis is focused on the algorithm of automatic detection of the optical disk in retinal images. It briefly describes the anatomy of the human eye and the principles of scanning the ocular background. The following describes the optical disk segmentation methods. Selected methods are implemented in MATLAB and optimized using a genetic algorithm. A total of five methods were introduced and optimized on the HRF dataset and two experimental datasets.
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Segmentation of optic disc in retinal image data
Juráček, Radek ; Mézl, Martin (referee) ; Odstrčilík, Jan (advisor)
This bachelor thesis is focused on the algorithm of automatic detection of the optical disk in retinal images. It briefly describes the anatomy of the human eye and the principles of scanning the ocular background. The following describes the optical disk segmentation methods. Selected methods are implemented in MATLAB and optimized using a genetic algorithm. A total of five methods were introduced and optimized on the HRF dataset and two experimental datasets.
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Overview of Actual Approaches to Optimization
Hudecová, Patrícia ; Šůstek, Martin (referee) ; Zbořil, František (advisor)
This work aimed to study some of the optimization algorithms inspired by nature and to test their success in finding the extreme of a function on various functions. Four algorithms were selected, namely the bat algorithm, the firefly algorithm, the flower pollination algorithm, and the black hole algorithm. The Griewank function, the Rastringin function, and the Rosenbrock function were chosen as test functions for finding the extreme of the function. The work contains a description of individual algorithms, a description of test functions and a description of the experiments, and an evaluation of the success of the algorithms.
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