Determining clonning templates of CNN via moga: Edge detection
Selami Parmaksızoğlu, Enis Günay, Mustafa Alçı · 2011
Recent scientific and technological developments allow a dynamical evaluation method, named Cellular Neural Networks (CNNs), and enable to use it in various areas mostly in image processing. It seems to be an optimization problem to determine the cloning templates as network parameters that obtain the desired output in CNNs. In this work, to achieve edge detection in colored images via CNNs, Multi Object Genetic Algorithm (MOGA) is used to determine the cloning templates. Two different methods are used to obtain edge detection in colored images and results are compared with classical edge detection techniques.