Semantic segmentation using Three-Dimensional Cellular Evolutionary Networks

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@InProceedings{Shimazaki:2016:SMC,

• author = "Ken Shimazaki and Tomoharu Nagao",
• booktitle = "2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC)",
• title = "Semantic segmentation using Three-Dimensional Cellular Evolutionary Networks",
• year = "2016",
• pages = "001411--001416",
• abstract = "Image segmentation and image recognition are challenging processes, and the methods of merging those two processes like semantic segmentation have been studied. However, it is a lot of labour to construct the processes of segmentation and recognition manually, so automatic construction of those approaches using machine learning or evolutionary computation have been proposed. In this paper, we propose a model of pixel-wise image segmentation and recognition using Cellular Evolutionary Networks (CEN). Our proposed model is composed of a regular array of the identical feed forward networks, represented in Cartesian Genetic Programming (CGP), and each CGP connects with neighbour CGPs. Besides, we also propose a new model of CEN called Three-Dimensional Cellular Evolutionary Networks (3D-CEN), which is composed of multiple CENs. We applied CEN and 3D-CEN to road scene images and verified the effectiveness of our method, and experimental results showed that our new model acquired better performance compared with other methods if efficient evolution for CEN is done.",
• keywords = "genetic algorithms, genetic programming, cartesian genetic programming",
• DOI = "doi:10.1109/SMC.2016.7844434",
• month = oct,
• notes = "Also known as \cite{7844434}",

}

Genetic Programming entries for Ken Shimazaki Tomoharu Nagao

Citations