http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-107680081-B

Outgoing Links

Predicate Object
classificationCPCAdditional http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T2207-10036
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T2207-20084
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T2207-20081
classificationCPCInventive http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T7-0002
classificationIPCInventive http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06T7-00
filingDate 2017-09-08-04:00^^<http://www.w3.org/2001/XMLSchema#date>
grantDate 2020-06-23-04:00^^<http://www.w3.org/2001/XMLSchema#date>
publicationDate 2020-06-23-04:00^^<http://www.w3.org/2001/XMLSchema#date>
publicationNumber CN-107680081-B
titleOfInvention Hyperspectral image unmixing method based on convolutional neural network
abstract The invention discloses a hyperspectral image unmixing method based on a convolutional neural network, which mainly solves the problems of low unmixing precision of hyperspectral images, complex model, long time consumption and low efficiency in the hyperspectral image unmixing process in the prior art. The problem. The steps of the present invention are: acquiring a data matrix, preprocessing the data matrix, constructing a convolutional neural network with a 10-layer structure containing a pixel-based fuzzy classification structure, training the convolutional neural network, fuzzy classification, and outputting the convolutional neural network The results are normalized to obtain unmixed results. The present invention introduces a convolutional neural network model based on a pixel-based fuzzy classification structure, and has the advantages of high unmixing accuracy, simple model, low calculation amount and easy implementation.
priorityDate 2017-09-08-04:00^^<http://www.w3.org/2001/XMLSchema#date>
type http://data.epo.org/linked-data/def/patent/Publication

Incoming Links

Predicate Subject
isDiscussedBy http://rdf.ncbi.nlm.nih.gov/pubchem/substance/SID419512635
http://rdf.ncbi.nlm.nih.gov/pubchem/compound/CID962

Total number of triples: 15.