http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-107424147-A
Outgoing Links
Predicate | Object |
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assignee | http://rdf.ncbi.nlm.nih.gov/pubchem/patentassignee/MD5_2d09298f58671950aeb56a0514d3e5e2 |
classificationCPCAdditional | http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T2207-20081 |
classificationCPCInventive | http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T7-0002 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F18-23213 |
classificationIPCInventive | http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06K9-62 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06T7-00 |
filingDate | 2017-07-03-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
inventor | http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_183ccc655f423133105e76b69cfbf038 http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_5bc3b8f32f89c269250f031638de4116 |
publicationDate | 2017-12-01-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
publicationNumber | CN-107424147-A |
titleOfInvention | Pattern Defect Recognition and Location Method Based on Latent Dirichlet Distribution Model |
abstract | The invention discloses a method for identifying and locating graphic defects based on a hidden Dirichlet distribution model, which includes a training phase and a testing phase. Features, forming a chaotic feature vector, a training image is represented by a chaotic feature vector matrix; all trained chaotic feature vector matrices are clustered by the k-means clustering method to form a codebook, and then a primary histogram is formed through the codebook; The high-level histogram is obtained by learning the primary histogram through the hidden Dirichlet distribution model, and the training image is represented by the high-level histogram; the test phase includes the following steps: the test image is represented by the high-level histogram; the above-mentioned high-level histogram is calculated The similarity between the graph and the advanced histogram is used to judge the defect category and location of the test image. |
isCitedBy | http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-111258905-A |
priorityDate | 2017-07-03-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
type | http://data.epo.org/linked-data/def/patent/Publication |
Incoming Links
Predicate | Subject |
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isDiscussedBy | http://rdf.ncbi.nlm.nih.gov/pubchem/compound/CID25572 http://rdf.ncbi.nlm.nih.gov/pubchem/substance/SID415713197 |
Total number of triples: 18.