SENSOR ARRAY FOR GENERATING NETWORK LEARNING POPULATIONS USING LIMITED SAMPLE SIZES
A method for generating a training data set for machine learning includes disposing a first sample component in or about a sensing apparatus. The sensing apparatus includes a plurality of sensors, each sensor being disposed at a unique position and angle relative to the first sample component. The m...
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creator | Kerwin, Kevin Richard |
description | A method for generating a training data set for machine learning includes disposing a first sample component in or about a sensing apparatus. The sensing apparatus includes a plurality of sensors, each sensor being disposed at a unique position and angle relative to the first sample component. The method captures a first sensor output of each sensor, thereby generating a first training data set including a first plurality of sensor outputs. The method then manipulates at least one of the first sample component and an environment within the sensing apparatus, and captures an additional sensor output of each sensor, thereby generating an additional training data set including an additional plurality of sensor outputs. The method then reiterates the step of manipulating the at least one of the first sample component and the environment within the sensing apparatus and capturing the additional sensor output of each sensor. Finally, the method merges each of the sensor outputs in the first training data set and each additional training data set, thereby generating a full machine learning training set. |
format | Patent |
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The sensing apparatus includes a plurality of sensors, each sensor being disposed at a unique position and angle relative to the first sample component. The method captures a first sensor output of each sensor, thereby generating a first training data set including a first plurality of sensor outputs. The method then manipulates at least one of the first sample component and an environment within the sensing apparatus, and captures an additional sensor output of each sensor, thereby generating an additional training data set including an additional plurality of sensor outputs. The method then reiterates the step of manipulating the at least one of the first sample component and the environment within the sensing apparatus and capturing the additional sensor output of each sensor. Finally, the method merges each of the sensor outputs in the first training data set and each additional training data set, thereby generating a full machine learning training set.</description><language>eng</language><subject>CALCULATING ; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS ; COMPUTING ; COUNTING ; PHYSICS</subject><creationdate>2020</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=20201029&DB=EPODOC&CC=US&NR=2020342309A1$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,780,885,25563,76318</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20201029&DB=EPODOC&CC=US&NR=2020342309A1$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>Kerwin, Kevin Richard</creatorcontrib><title>SENSOR ARRAY FOR GENERATING NETWORK LEARNING POPULATIONS USING LIMITED SAMPLE SIZES</title><description>A method for generating a training data set for machine learning includes disposing a first sample component in or about a sensing apparatus. The sensing apparatus includes a plurality of sensors, each sensor being disposed at a unique position and angle relative to the first sample component. The method captures a first sensor output of each sensor, thereby generating a first training data set including a first plurality of sensor outputs. The method then manipulates at least one of the first sample component and an environment within the sensing apparatus, and captures an additional sensor output of each sensor, thereby generating an additional training data set including an additional plurality of sensor outputs. The method then reiterates the step of manipulating the at least one of the first sample component and the environment within the sensing apparatus and capturing the additional sensor output of each sensor. Finally, the method merges each of the sensor outputs in the first training data set and each additional training data set, thereby generating a full machine learning training set.</description><subject>CALCULATING</subject><subject>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</subject><subject>COMPUTING</subject><subject>COUNTING</subject><subject>PHYSICS</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2020</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNrjZAgOdvUL9g9ScAwKcoxUcAOy3F39XIMcQzz93BX8XEPC_YO8FXxcHYP8QAIB_gGhPkA5f79ghdBgkIiPp69niKuLQrCjb4CPq0KwZ5RrMA8Da1piTnEqL5TmZlB2cw1x9tBNLciPTy0uSExOzUstiQ8NNjIwMjA2MTI2sHQ0NCZOFQD98DE6</recordid><startdate>20201029</startdate><enddate>20201029</enddate><creator>Kerwin, Kevin Richard</creator><scope>EVB</scope></search><sort><creationdate>20201029</creationdate><title>SENSOR ARRAY FOR GENERATING NETWORK LEARNING POPULATIONS USING LIMITED SAMPLE SIZES</title><author>Kerwin, Kevin Richard</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_US2020342309A13</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>eng</language><creationdate>2020</creationdate><topic>CALCULATING</topic><topic>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</topic><topic>COMPUTING</topic><topic>COUNTING</topic><topic>PHYSICS</topic><toplevel>online_resources</toplevel><creatorcontrib>Kerwin, Kevin Richard</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Kerwin, Kevin Richard</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>SENSOR ARRAY FOR GENERATING NETWORK LEARNING POPULATIONS USING LIMITED SAMPLE SIZES</title><date>2020-10-29</date><risdate>2020</risdate><abstract>A method for generating a training data set for machine learning includes disposing a first sample component in or about a sensing apparatus. The sensing apparatus includes a plurality of sensors, each sensor being disposed at a unique position and angle relative to the first sample component. The method captures a first sensor output of each sensor, thereby generating a first training data set including a first plurality of sensor outputs. The method then manipulates at least one of the first sample component and an environment within the sensing apparatus, and captures an additional sensor output of each sensor, thereby generating an additional training data set including an additional plurality of sensor outputs. The method then reiterates the step of manipulating the at least one of the first sample component and the environment within the sensing apparatus and capturing the additional sensor output of each sensor. 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subjects | CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING PHYSICS |
title | SENSOR ARRAY FOR GENERATING NETWORK LEARNING POPULATIONS USING LIMITED SAMPLE SIZES |
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