http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-108229366-B
Outgoing Links
| Predicate | Object |
|---|---|
| classificationCPCInventive | http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G01S17-931 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06V20-58 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G01S17-86 |
| classificationIPCInventive | http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06K9-00 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06K9-62 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G01S17-931 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G01S17-86 |
| filingDate | 2017-12-28-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| grantDate | 2021-12-14-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationDate | 2021-12-14-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationNumber | CN-108229366-B |
| titleOfInvention | Deep learning vehicle-mounted obstacle detection method based on radar and image data fusion |
| abstract | The invention discloses a target detection algorithm based on intelligent device sensor data fusion and deep learning, which enriches data characteristic types which can be sensed by a detection model through fused radar point cloud data and camera data. Model training is carried out through fusion of data channels with different configurations, and the optimal channel configuration is selected, so that the detection accuracy is improved, and meanwhile, the calculation power consumption is reduced. The channel configuration suitable for the real situation is determined by testing the real data, and the purpose of processing the fusion data by using the Yolo deep convolution neural network model and detecting the target obstacle of the road scene is achieved. |
| priorityDate | 2017-12-28-04:00^^<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/SID419524163 http://rdf.ncbi.nlm.nih.gov/pubchem/compound/CID14284 |
Total number of triples: 17.