http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-108052977-B
Outgoing Links
| Predicate | Object |
|---|---|
| classificationCPCAdditional | http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06V2201-03 |
| classificationCPCInventive | http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F18-24 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06V10-267 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F18-214 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F18-25 |
| classificationIPCInventive | http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06K9-34 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06K9-62 |
| filingDate | 2017-12-15-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| grantDate | 2021-09-14-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationDate | 2021-09-14-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationNumber | CN-108052977-B |
| titleOfInvention | Deep learning classification method of mammography images based on lightweight neural network |
| abstract | The invention relates to a deep learning classification method for mammography images based on a lightweight neural network. The method uses an image classification algorithm based on deep learning to achieve breast density classification for mammography images, and uses a deep learning framework based on a lightweight neural network. The method of the invention significantly improves the adaptability on small-scale image data sets, thereby improves the accuracy and processing speed of breast density classification, and can realize automatic breast density classification of mammography target images. |
| priorityDate | 2017-12-15-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| type | http://data.epo.org/linked-data/def/patent/Publication |
Incoming Links
Total number of triples: 18.