Immunity chromatography test strip quantitation detection method based on deep reliability network
A quantitative detection method and deep confidence network technology, applied in neural learning methods, biological neural network models, measurement devices, etc., can solve the problems of limited application scope, lack of information, and inability to meet the requirements of practical applications, and achieve good image segmentation. effect, improve accuracy, overcome the effect of internal and external interference factors
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[0028] The present invention will be further described below in conjunction with accompanying drawing and specific embodiment, as figure 1 Shown, a kind of immunochromatographic test strip quantitative detection method based on deep belief network, comprises the following steps:
[0029] 1. Collect images of several immunochromatographic test strips with different concentrations of sample liquid as training images, preprocess them, and extract the target area including the detection line and quality control line respectively. The size of the target area is 180×90.
[0030] 2. Divide the target area into two parts, one is the detection line and its background, the other is the quality control line and its background, both of which are 50×90 in size. Taking pixels as the sample unit, select the appropriate network input feature quantity, and calculate the input quantity of each sample. The input feature quantity considers three factors, including the following steps:
[0031] 2...
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