http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-111833325-A

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filingDate 2020-07-09-04:00^^<http://www.w3.org/2001/XMLSchema#date>
inventor http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_8194a6e4974cb932a30c056acf63ab05
publicationDate 2020-10-27-04:00^^<http://www.w3.org/2001/XMLSchema#date>
publicationNumber CN-111833325-A
titleOfInvention A deep learning-based detection method and system for colloidal gold reagent strips
abstract The invention discloses a method and system for detecting colloidal gold reagent strips based on deep learning, and relates to the technical field of colloidal gold reagent strip detection. The acquired images to be detected are sent to a trained deep learning neural network model for image segmentation , obtain the standard color card image, the colloidal gold reagent strip image and the two-dimensional code image carrying the standard parameters of the image; analyze the two-dimensional code image to obtain the standard gray value, and analyze the standard color card to obtain the read gray value. The standard gray value is the benchmark, and the gray value calibration curve of the read gray value is fitted; the color gray value is obtained by analyzing the image of the colloidal gold reagent strip, and the color gray value is calculated by the gray value calibration curve. Correction to obtain the corrected color gray value, matching the corrected color gray value with the preset biological calculation algorithm to obtain the detection result of the colloidal gold reagent strip; using the detection method of the present application improves the performance of the colloidal gold reagent The accuracy of the detection result of the bar image.
isCitedBy http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-114441511-A
priorityDate 2020-07-09-04:00^^<http://www.w3.org/2001/XMLSchema#date>
type http://data.epo.org/linked-data/def/patent/Publication

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Total number of triples: 26.