SYSTEMS AND METHODS FOR CROSS-DOMAIN TRAINING OF SENSING-SYSTEM-MODEL INSTANCES
Disclosed herein are systems and methods for cross-domain training of sensing-system-model instances. In an embodiment, a system receives, via a first application programming interface (API), an input-dataset selection identifying an input dataset, which includes a plurality of dataframes that are i...
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| creator | Jarquin Arroyo, Julio Fernando Alvarez Martinez, Ignacio Javier |
| description | Disclosed herein are systems and methods for cross-domain training of sensing-system-model instances. In an embodiment, a system receives, via a first application programming interface (API), an input-dataset selection identifying an input dataset, which includes a plurality of dataframes that are in a first dataframe format and that have annotations corresponding to one or more sensing tasks performed with respect to the dataframes. The system executes a plurality of dataframe-transformation functions to convert the plurality of dataframes of the input dataset into a predetermined dataframe format. The system trains an instance of a first machine-learning model using the converted dataframes of the input dataset to perform at least a subset of the one or more sensing tasks. The system outputs, via the first API, one or more model-validation metrics pertaining to the training of the instance of the first machine-learning model. |
| format | Patent |
| fullrecord | <record><control><sourceid>epo_EVB</sourceid><recordid>TN_cdi_epo_espacenet_US2022111864A1</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>US2022111864A1</sourcerecordid><originalsourceid>FETCH-epo_espacenet_US2022111864A13</originalsourceid><addsrcrecordid>eNrjZPAPjgwOcfUNVnD0c1HwdQ3x8HcJVnDzD1JwDvIPDtZ18fd19PRTCAkCkp5-7gr-bgrBrn7BQKYuRKOur7-Lq4-Cp19wiKOfs2swDwNrWmJOcSovlOZmUHZzDXH20E0tyI9PLS5ITE7NSy2JDw02MjAyMjQ0tDAzcTQ0Jk4VACMIL_U</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>patent</recordtype></control><display><type>patent</type><title>SYSTEMS AND METHODS FOR CROSS-DOMAIN TRAINING OF SENSING-SYSTEM-MODEL INSTANCES</title><source>esp@cenet</source><creator>Jarquin Arroyo, Julio Fernando ; Alvarez Martinez, Ignacio Javier</creator><creatorcontrib>Jarquin Arroyo, Julio Fernando ; Alvarez Martinez, Ignacio Javier</creatorcontrib><description>Disclosed herein are systems and methods for cross-domain training of sensing-system-model instances. In an embodiment, a system receives, via a first application programming interface (API), an input-dataset selection identifying an input dataset, which includes a plurality of dataframes that are in a first dataframe format and that have annotations corresponding to one or more sensing tasks performed with respect to the dataframes. The system executes a plurality of dataframe-transformation functions to convert the plurality of dataframes of the input dataset into a predetermined dataframe format. The system trains an instance of a first machine-learning model using the converted dataframes of the input dataset to perform at least a subset of the one or more sensing tasks. The system outputs, via the first API, one or more model-validation metrics pertaining to the training of the instance of the first machine-learning model.</description><language>eng</language><subject>CALCULATING ; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS ; COMPUTING ; CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE ORDIFFERENT FUNCTION ; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES ; COUNTING ; HANDLING RECORD CARRIERS ; PERFORMING OPERATIONS ; PHYSICS ; PRESENTATION OF DATA ; RECOGNITION OF DATA ; RECORD CARRIERS ; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TOTHE CONTROL OF A PARTICULAR SUB-UNIT ; TRANSPORTING ; VEHICLES IN GENERAL</subject><creationdate>2022</creationdate><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20220414&DB=EPODOC&CC=US&NR=2022111864A1$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,776,881,25542,76516</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20220414&DB=EPODOC&CC=US&NR=2022111864A1$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>Jarquin Arroyo, Julio Fernando</creatorcontrib><creatorcontrib>Alvarez Martinez, Ignacio Javier</creatorcontrib><title>SYSTEMS AND METHODS FOR CROSS-DOMAIN TRAINING OF SENSING-SYSTEM-MODEL INSTANCES</title><description>Disclosed herein are systems and methods for cross-domain training of sensing-system-model instances. In an embodiment, a system receives, via a first application programming interface (API), an input-dataset selection identifying an input dataset, which includes a plurality of dataframes that are in a first dataframe format and that have annotations corresponding to one or more sensing tasks performed with respect to the dataframes. The system executes a plurality of dataframe-transformation functions to convert the plurality of dataframes of the input dataset into a predetermined dataframe format. The system trains an instance of a first machine-learning model using the converted dataframes of the input dataset to perform at least a subset of the one or more sensing tasks. The system outputs, via the first API, one or more model-validation metrics pertaining to the training of the instance of the first machine-learning model.</description><subject>CALCULATING</subject><subject>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</subject><subject>COMPUTING</subject><subject>CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE ORDIFFERENT FUNCTION</subject><subject>CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES</subject><subject>COUNTING</subject><subject>HANDLING RECORD CARRIERS</subject><subject>PERFORMING OPERATIONS</subject><subject>PHYSICS</subject><subject>PRESENTATION OF DATA</subject><subject>RECOGNITION OF DATA</subject><subject>RECORD CARRIERS</subject><subject>ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TOTHE CONTROL OF A PARTICULAR SUB-UNIT</subject><subject>TRANSPORTING</subject><subject>VEHICLES IN GENERAL</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2022</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNrjZPAPjgwOcfUNVnD0c1HwdQ3x8HcJVnDzD1JwDvIPDtZ18fd19PRTCAkCkp5-7gr-bgrBrn7BQKYuRKOur7-Lq4-Cp19wiKOfs2swDwNrWmJOcSovlOZmUHZzDXH20E0tyI9PLS5ITE7NSy2JDw02MjAyMjQ0tDAzcTQ0Jk4VACMIL_U</recordid><startdate>20220414</startdate><enddate>20220414</enddate><creator>Jarquin Arroyo, Julio Fernando</creator><creator>Alvarez Martinez, Ignacio Javier</creator><scope>EVB</scope></search><sort><creationdate>20220414</creationdate><title>SYSTEMS AND METHODS FOR CROSS-DOMAIN TRAINING OF SENSING-SYSTEM-MODEL INSTANCES</title><author>Jarquin Arroyo, Julio Fernando ; Alvarez Martinez, Ignacio Javier</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_US2022111864A13</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>eng</language><creationdate>2022</creationdate><topic>CALCULATING</topic><topic>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</topic><topic>COMPUTING</topic><topic>CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE ORDIFFERENT FUNCTION</topic><topic>CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES</topic><topic>COUNTING</topic><topic>HANDLING RECORD CARRIERS</topic><topic>PERFORMING OPERATIONS</topic><topic>PHYSICS</topic><topic>PRESENTATION OF DATA</topic><topic>RECOGNITION OF DATA</topic><topic>RECORD CARRIERS</topic><topic>ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TOTHE CONTROL OF A PARTICULAR SUB-UNIT</topic><topic>TRANSPORTING</topic><topic>VEHICLES IN GENERAL</topic><toplevel>online_resources</toplevel><creatorcontrib>Jarquin Arroyo, Julio Fernando</creatorcontrib><creatorcontrib>Alvarez Martinez, Ignacio Javier</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Jarquin Arroyo, Julio Fernando</au><au>Alvarez Martinez, Ignacio Javier</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>SYSTEMS AND METHODS FOR CROSS-DOMAIN TRAINING OF SENSING-SYSTEM-MODEL INSTANCES</title><date>2022-04-14</date><risdate>2022</risdate><abstract>Disclosed herein are systems and methods for cross-domain training of sensing-system-model instances. In an embodiment, a system receives, via a first application programming interface (API), an input-dataset selection identifying an input dataset, which includes a plurality of dataframes that are in a first dataframe format and that have annotations corresponding to one or more sensing tasks performed with respect to the dataframes. The system executes a plurality of dataframe-transformation functions to convert the plurality of dataframes of the input dataset into a predetermined dataframe format. The system trains an instance of a first machine-learning model using the converted dataframes of the input dataset to perform at least a subset of the one or more sensing tasks. The system outputs, via the first API, one or more model-validation metrics pertaining to the training of the instance of the first machine-learning model.</abstract><oa>free_for_read</oa></addata></record> |
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| subjects | CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE ORDIFFERENT FUNCTION CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES COUNTING HANDLING RECORD CARRIERS PERFORMING OPERATIONS PHYSICS PRESENTATION OF DATA RECOGNITION OF DATA RECORD CARRIERS ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TOTHE CONTROL OF A PARTICULAR SUB-UNIT TRANSPORTING VEHICLES IN GENERAL |
| title | SYSTEMS AND METHODS FOR CROSS-DOMAIN TRAINING OF SENSING-SYSTEM-MODEL INSTANCES |
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