http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-111272290-B
Outgoing Links
| Predicate | Object |
|---|---|
| classificationCPCAdditional | http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G01J2005-0077 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T2207-20084 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T2207-20081 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T2207-10048 |
| classificationCPCInventive | http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G01J5-00 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T7-80 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G01J5-80 |
| classificationIPCInventive | http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G01J5-48 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06T7-80 |
| filingDate | 2020-03-13-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| grantDate | 2022-07-19-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationDate | 2022-07-19-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationNumber | CN-111272290-B |
| titleOfInvention | Calibration method and device for temperature measurement infrared thermal imager based on deep neural network |
| abstract | The invention discloses a method for calibrating a temperature measuring thermal imager based on a deep neural network, comprising the following steps: collecting background infrared images under different temperature combination conditions by using an infrared thermal imager to be calibrated; The database trains the deep neural network and updates the parameters of the deep neural network; uses the trained deep neural network to calibrate the temperature field image corresponding to the infrared image. The invention also discloses a temperature measuring thermal imager calibration device based on the deep neural network. The present invention uses the deep neural network to establish the mapping relationship between the temperature of the infrared lens, the working temperature of the focal plane of the detector, the pixel value of the infrared image and the temperature measurement value, updates the parameters of the deep neural network, and uses the updated deep neural network to estimate the temperature measurement. Therefore, the temperature measurement infrared thermal imager has the advantages of no mechanical baffle, simple temperature measurement operation, and high temperature measurement accuracy. |
| priorityDate | 2020-03-13-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| type | http://data.epo.org/linked-data/def/patent/Publication |
Incoming Links
Total number of triples: 20.