http://rdf.ncbi.nlm.nih.gov/pubchem/patent/WO-2021097426-A1
Outgoing Links
| Predicate | Object |
|---|---|
| assignee | http://rdf.ncbi.nlm.nih.gov/pubchem/patentassignee/MD5_88e6dea6a714136253001a5dd61cc62f |
| classificationCPCInventive | http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N3-08 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N3-045 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N5-04 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N3-04 |
| classificationIPCInventive | http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06N3-04 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06N3-08 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06N20-00 |
| filingDate | 2020-11-16-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| inventor | http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_cb50ce96045adac9902ceef8644e5fd9 http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_361e9bfafdb41d770304105cb1a2abf9 |
| publicationDate | 2021-05-20-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationNumber | WO-2021097426-A1 |
| titleOfInvention | Systems and methods for training neural networks on a cloud server using sensory data collected by robots |
| abstract | Systems and methods for training neural networks on a cloud server using sensory data collected by plurality of robots. According to at least one non-limiting exemplary embodiment, a system for training a model is disclosed. The model may be derived from one or more trained neural networks, the neural networks being trained using data collected by one or more robots. Advantageously, data collection by robots may enhance consistency, reliability, and quality of data received for use in training one or more neural networks. The model may be utilized by robots, upon sufficient training of the neural networks, such that the robots may identify features within their environments. Advantageously, the model may be trained on a cloud server and utilized by individual robots for use in enhancing autonomy of the robots, wherein the utilization of the model requires significantly fewer computational resources than training of the neural networks to develop the model. |
| priorityDate | 2019-11-15-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| type | http://data.epo.org/linked-data/def/patent/Publication |
Incoming Links
Total number of triples: 38.