http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-111402259-B
Outgoing Links
| Predicate | Object |
|---|---|
| classificationCPCAdditional | http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T2207-10088 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T2207-30016 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T2207-30096 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T2207-20081 |
| classificationCPCInventive | http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T7-10 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N3-08 |
| classificationIPCInventive | http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06N3-08 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06T7-10 |
| filingDate | 2020-03-23-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| grantDate | 2022-07-15-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationDate | 2022-07-15-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationNumber | CN-111402259-B |
| titleOfInvention | A Brain Tumor Segmentation Method Based on Multi-Hierarchical Relational Learning Network |
| abstract | The invention proposes an advanced multi-level structure relation learning network for segmenting brain tumor data. In each sub-network, an environmental information mining module is introduced between the encoder and the decoder, and dual self-attention mechanism and spatial interaction learning are used to mine environmental information within a single domain and between different domains, respectively. |
| priorityDate | 2020-03-23-04:00^^<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/CID5572 http://rdf.ncbi.nlm.nih.gov/pubchem/substance/SID419502926 |
Total number of triples: 18.