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Swarm Intelligence-Based Methodology for Scanning Electron Microscope Image Segmentation of Solid Oxide Fuel Cell Anode
2021
Energies
Segmentation of images from scanning electron microscope, especially multiphase, poses a drawback in their microstructure quantification process. The labeling process must be automatized due to the time consumption and irreproducibility of the manual labeling procedure. Here we show a swarm intelligence-driven filtration methodology performed on raw solid oxide fuel cell anode's material images to improve the segmentation methods' performance. The methodology focused on two significant parts of
doi:10.3390/en14113055
fatcat:7zuohgdm2nfgxg6kf734iwdhoy