| Predicate |
Object |
| assignee |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentassignee/MD5_91334899bf1fd898947baee28356778d |
| classificationCPCAdditional |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T2207-20084
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T2207-20081 |
| classificationCPCInventive |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T5-30
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T7-13
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F18-24
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T5-007
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N3-04
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N3-08
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06F18-214 |
| classificationIPCInventive |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06V10-82
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06N3-04
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06V20-52
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06V10-774
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06K9-62
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06T5-00
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06V10-44
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06V10-764
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06T7-13
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06N3-08
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06T5-30 |
| filingDate |
2021-10-13-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| inventor |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_c5bbf3e9c12e29e956344aa7942516d6 |
| publicationDate |
2022-02-22-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationNumber |
CN-114078229-A |
| titleOfInvention |
A method for detecting floating objects in a river |
| abstract |
The invention discloses a method for detecting floating objects in a river channel. The pixel area in the real-time video of a monitoring camera that needs to be detected floating in a river channel is selected for image processing, and then the pictures are classified into water waves and suspected floating objects through a classification neural network. The feature extraction neural network obtains the feature value vector of the picture; each suspected floating object is tracked by the Deepsort target tracker, and when the tracking target moves in the picture, the target is identified as a floating object; the floating object in the river can be found in time Make judgments for the next salvage work, effectively avoiding the need to invest in inspectors in rivers without floating objects, reducing labor costs and improving salvage efficiency. |
| priorityDate |
2021-10-13-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| type |
http://data.epo.org/linked-data/def/patent/Publication |