http://rdf.ncbi.nlm.nih.gov/pubchem/patent/US-2022414864-A1

Outgoing Links

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assignee http://rdf.ncbi.nlm.nih.gov/pubchem/patentassignee/MD5_79352cfc0b3398827887984c3be659d6
classificationCPCAdditional http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T2207-30128
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http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T2207-20081
classificationCPCInventive http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06T7-0008
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G01N33-02
http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/A23P30-20
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classificationIPCInventive http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G01N33-02
http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06T7-00
filingDate 2022-06-14-04:00^^<http://www.w3.org/2001/XMLSchema#date>
inventor http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_b830155bd1fa4eb7e9f5f604d2ba84fb
http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_dc039d166066936d1f608dde81e69d81
publicationDate 2022-12-29-04:00^^<http://www.w3.org/2001/XMLSchema#date>
publicationNumber US-2022414864-A1
titleOfInvention Devices, systems, and methods for virtual bulk density sensing
abstract Devices, systems, and methods for real-time food production are disclosed. Extrusion can include including evaluating and controlling one or more production devices to produce desirable food products. Evaluation can be performed by an evaluation system including a convolutional neural network to determine a bulk density value. Control can be performed by a machine learning model on the basis of the bulk density value. Control can include determination of real-time settings for production device parameters.
priorityDate 2021-06-25-04:00^^<http://www.w3.org/2001/XMLSchema#date>
type http://data.epo.org/linked-data/def/patent/Publication

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Total number of triples: 21.