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- W3217071720 abstract "The ovulation test strip is a tool for ovulation detection. At present, many APPs have been developed to analyze the photos taken from ovulation test strips to read the T/C ratio for detecting the level of luteinizing hormone (LH) in human urine. However, in the process of detecting the T and C lines, the background colors of the area near the T line or C line may be red, the T and C lines are sometimes fuzzy, and the colors of the T and C lines are sometimes distributed unevenly. In these cases, these APPs will be confronting difficulty to accurately detect the T and C lines and further read their ratio. To solve these problems, we proposed a method that consists of two steps. The first step is to use Mask R-CNN to locate the T and C lines, and the second step is to use a trained Pseudo-Siamese ratio reading network (PSRRNet) to read the ratio value based on the output results of the first step. The proposed PSRRNet consists of a Pseudo-Siamese network for simultaneously extracting the features of the T and C lines and a fully connected network to use the extracted features to predict the T/C ratio value. The experimental results illustrated that the proposed method suits to handle ovulation test strip reading." @default.
- W3217071720 created "2021-12-06" @default.
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- W3217071720 date "2021-01-01" @default.
- W3217071720 modified "2023-09-23" @default.
- W3217071720 title "T Line and C Line Detection and Ratio Reading of the Ovulation Test Strip Based on Deep Learning" @default.
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- W3217071720 doi "https://doi.org/10.1007/978-3-030-91608-4_60" @default.
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