http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-109460777-A
Outgoing Links
| Predicate | Object |
|---|---|
| assignee | http://rdf.ncbi.nlm.nih.gov/pubchem/patentassignee/MD5_e0e7cc202b6c1f07e2b996b4f063559b |
| classificationCPCInventive | http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N3-045 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F18-2411 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F18-214 |
| classificationIPCInventive | http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06N3-04 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06K9-62 |
| filingDate | 2018-10-11-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| inventor | http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_8f36ee0093541d003a774eb13d33380f http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_d24cf6f323da22da2e46fe1b28523745 |
| publicationDate | 2019-03-12-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationNumber | CN-109460777-A |
| titleOfInvention | Image classification method, device and computer-readable storage medium |
| abstract | The present application relates to a picture classification method, device, computer-readable storage medium and computer equipment. By acquiring each picture to be classified, inputting each picture to be classified into a feature extraction model, a feature vector of each picture to be classified is obtained, and each picture to be classified is obtained. The distribution of the feature vector of the picture to be classified in the feature space, and according to the distribution, the feature space is divided into a limited domain of categories to obtain a picture classification result. By extracting the feature vectors of the pictures to be classified, the distribution of the feature vectors of the pictures to be classified in the feature space is obtained, and the category is divided into a finite field based on the distribution of the feature space, and the non-target pictures are removed from the target pictures. The impact of the target image on the classification accuracy of the target image solves the problem that all images that need to be classified are composed of N different target images and non-target images, resulting in low accuracy and precision of image classification. |
| isCitedBy | http://rdf.ncbi.nlm.nih.gov/pubchem/patent/WO-2020228179-A1 http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-111242230-A |
| priorityDate | 2018-10-11-04:00^^<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/compound/CID5281875 http://rdf.ncbi.nlm.nih.gov/pubchem/substance/SID419517547 |
Total number of triples: 19.