Geometric feature extraction in nanofiber membrane image based on convolution neural network for surface roughness prediction.

ABSTRACT: As a technique in artificial intelligence, a convolution neural network model has been utilized to extract average surface roughness from the geometric characteristics of a membrane image featuring micro- and nanostructures. For surface roughness measurement, e.g. atomic force microscopy and optical profiler, the previous methods have been performed to analyze a porous membrane surface on an interest of region with a few micrometers of the restricted area according to the depth resolution. However, an image from the scanning electron microscope, combined with the feature extraction process, provides clarity on surface roughness for multiple areas with various depth resolutions. Through image preprocessing, the geometric pattern is elucidated by amplifying the disparity in pixel intensity v

SUBMITTER: Kang DH 

PROVIDER: S-EPMC11336630 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature