http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-103366175-B
Outgoing Links
| Predicate | Object |
|---|---|
| classificationIPCInventive | http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06K9-46 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06F17-30 |
| filingDate | 2013-07-14-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| grantDate | 2016-04-13-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationDate | 2016-04-13-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationNumber | CN-103366175-B |
| titleOfInvention | Based on the scene image classification method that potential Di Li Cray distributes |
| abstract | The invention discloses a kind of scene image classification method of distributing based on potential Di Li Cray, mainly solve longer and that nicety of grading declines under the prerequisite shortening the classification time problem of existing full supervision scene image classification classification time.Implementation step is: the hue, saturation, intensity, the notable feature figure that obtain every width natural image; The dense sampling of grid is carried out respectively to described characteristic pattern, obtains its Grid Sampling point; Each Grid Sampling point is extracted to the SIFT feature of its peripheral region; K cluster is carried out to the SIFT feature of homogenous characteristics figure, generates visual dictionary; With visual dictionary, all characteristic patterns are quantified as visual document; Input to LDA model after visual document being connected in turn and obtain potential applications theme distribution; The potential applications theme distribution of all natural images is inputed to SVM classifier classify, obtain classification results.The present invention, compared with classical taxonomy method, improves nicety of grading, can be used for target identification while shortening the average classification time. |
| priorityDate | 2013-07-14-04:00^^<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/SID419517741 http://rdf.ncbi.nlm.nih.gov/pubchem/compound/CID5352425 |
Total number of triples: 12.