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classificationCPCInventive http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F16-2458
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G01N33-18
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N3-084
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http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06F16-2458
filingDate 2020-11-06-04:00^^<http://www.w3.org/2001/XMLSchema#date>
grantDate 2021-08-03-04:00^^<http://www.w3.org/2001/XMLSchema#date>
publicationDate 2021-08-03-04:00^^<http://www.w3.org/2001/XMLSchema#date>
publicationNumber CN-112162979-B
titleOfInvention A deep learning-based marine sediment testing system and method
abstract The invention belongs to the technical field of marine water quality testing, and in particular relates to a deep learning-based marine sediment testing system and method. The system includes: a marine remote sensing satellite ground station, a remote remote sensing satellite, and a feedback neural network connecting the marine remote sensing satellite ground station and the remote remote sensing satellite; the remote remote sensing satellites have two groups, namely the first remote remote sensing satellite and the second remote remote sensing satellite. Remote sensing satellites; the system further includes: the first remote remote sensing satellite and the second remote remote sensing satellite obtain electromagnetic wave characteristic data information of the ocean, and send the data information to a feedback neural network; the feedback neural network responds to the received data information Carry out feedback correction, correct data information errors, and send the corrected information errors to the remote sensing satellite ground station. It has the advantages of high intelligence and high accuracy.
priorityDate 2019-11-14-04:00^^<http://www.w3.org/2001/XMLSchema#date>
type http://data.epo.org/linked-data/def/patent/Publication

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