patent/WO-2022076587-A1

Predicate	Object
assignee	http://rdf.ncbi.nlm.nih.gov/pubchem/patentassignee/MD5_a68790a12228f5b99e176e8aacff640a
classificationCPCAdditional	http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T2200-24 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T2207-20084
classificationCPCInventive	http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T7-11 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T3-4046 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T3-0012
classificationIPCInventive	http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06T3-00 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06T3-40 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06T7-11
filingDate	2021-10-06-04:00^^<http://www.w3.org/2001/XMLSchema#date>
inventor	http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_1c6f5817875303ae36ac29c397874369
publicationDate	2022-04-14-04:00^^<http://www.w3.org/2001/XMLSchema#date>
publicationNumber	WO-2022076587-A1
titleOfInvention	Image generation using one or more neural networks
abstract	Apparatuses, systems, and techniques are presented to generate images. In at least one embodiment, one or more neural networks are used to adjust one or more aspect ratios of one or more objects of one or more images based, at least in part, on input from one or more users.
priorityDate	2020-10-08-04:00^^<http://www.w3.org/2001/XMLSchema#date>
type	http://data.epo.org/linked-data/def/patent/Publication

Predicate	Subject
isCitedBy	http://rdf.ncbi.nlm.nih.gov/pubchem/patent/US-2019147296-A1
isDiscussedBy	http://rdf.ncbi.nlm.nih.gov/pubchem/compound/CID11355923 http://rdf.ncbi.nlm.nih.gov/pubchem/substance/SID423390989 http://rdf.ncbi.nlm.nih.gov/pubchem/compound/CID22978774 http://rdf.ncbi.nlm.nih.gov/pubchem/substance/SID419701332

Total number of triples: 22.