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Automatic classification of cells in microscopic fecal images using convolutional neural networks
2019
Bioscience Reports
The analysis of fecal-type components for clinical diagnosis is important. The main examination involves the counting of red blood cells (RBCs), white blood cells (WBCs), and molds under the microscopic. With the development of machine vision, some vision-based detection schemes have been proposed. However, these methods have a single target for detection, with low detection efficiency and low accuracy. We proposed an algorithm to identify the visible image of fecal composition based on
doi:10.1042/bsr20182100
pmid:30872411
pmcid:PMC6449518
fatcat:7ssi4hrj4nai5ereejq6hwrcxa