| Predicate |
Object |
| assignee |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentassignee/MD5_17cc2e143e369f78bc7ac4166c326752 |
| classificationCPCAdditional |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T2207-20084
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T2207-20081
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T2207-30024
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T2207-10036 |
| classificationCPCInventive |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T5-003
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T7-0014
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N20-00
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T3-0075
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T5-50
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N3-045
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T3-40
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N3-08 |
| classificationIPCInventive |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06N20-00
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06N3-08
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/G06T7-00 |
| filingDate |
2019-09-27-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| grantDate |
2022-06-07-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| inventor |
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_aa45a063bfc8f999b9f0ff7f7f0bd4f1
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_426925d6bddea7c381fb84bfa17a3faf |
| publicationDate |
2022-06-07-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationNumber |
US-11354804-B1 |
| titleOfInvention |
Transforming multispectral images to enhanced resolution images enabled by machine learning |
| abstract |
Systems and methods for predicting images with enhanced spatial resolution using a neural network are provided herein. According to an aspect of the invention, a method includes accessing an input image of a biological sample, wherein the input image includes a first spatial resolution and a plurality of spectral images, and wherein each spectral image of the plurality of spectral images includes data from a different wavelength band at a different spectral channel; applying a trained artificial neural network to the input image; generating an output image at a second spatial resolution, wherein the second spatial resolution is higher than the first spatial resolution, and wherein the output image includes a fewer number of spectral channels than the plurality of spectral images included in the input image; and outputting the output image. |
| isCitedBy |
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/US-11501190-B2
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/US-11678034-B2
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/US-2022232175-A1
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/US-2021043331-A1
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/US-2021064845-A1
http://rdf.ncbi.nlm.nih.gov/pubchem/patent/US-2022004897-A1 |
| priorityDate |
2019-09-27-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| type |
http://data.epo.org/linked-data/def/patent/Publication |