OBJECT DETECTION USING ARTIFICIAL INTELLIGENCE

OBJECT DETECTION USING ARTIFICIAL INTELLIGENCE

A method of training a machine learning model includes training a primary part of a composite neural network to identify a primary segment of objects in a training image, freezing the primary part of the composite neural network after training the primary part of the composite neural network, and af...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: PERRY, Kristopher Glenn, BANSAL, Anurag, MAESTRE TRUEBA, Miguel Angel, OSTAP, Oleg
Format: Patent
Sprache:eng
Schlagworte:
CALCULATING
COMPUTING
COUNTING
PHYSICS
Online-Zugang:Volltext bestellen
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page
container_issue
container_start_page
container_title
container_volume
creator PERRY, Kristopher Glenn
BANSAL, Anurag
MAESTRE TRUEBA, Miguel Angel
OSTAP, Oleg
description A method of training a machine learning model includes training a primary part of a composite neural network to identify a primary segment of objects in a training image, freezing the primary part of the composite neural network after training the primary part of the composite neural network, and after freezing the primary part of the composite neural network, training, using activations of the primary part of the composite neural network, a secondary part of the composite neural network to identify a first subsegment of objects or a feature of the first subsegment of objects in the training image. The first subsegment of objects is a subset of the primary segment of objects.
format Patent
fullrecord <record><control><sourceid>epo_EVB</sourceid><recordid>TN_cdi_epo_espacenet_US2024169698A1</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>US2024169698A1</sourcerecordid><originalsourceid>FETCH-epo_espacenet_US2024169698A13</originalsourceid><addsrcrecordid>eNrjZNDzd_JydQ5RcHENAVKe_n4KocGefu4KjkEhnm6ezp6OPgqefiGuPj6e7q5-zq48DKxpiTnFqbxQmptB2c01xNlDN7UgPz61uCAxOTUvtSQ-NNjIwMjE0MzSzNLC0dCYOFUAfeomzg</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>patent</recordtype></control><display><type>patent</type><title>OBJECT DETECTION USING ARTIFICIAL INTELLIGENCE</title><source>esp@cenet</source><creator>PERRY, Kristopher Glenn ; BANSAL, Anurag ; MAESTRE TRUEBA, Miguel Angel ; OSTAP, Oleg</creator><creatorcontrib>PERRY, Kristopher Glenn ; BANSAL, Anurag ; MAESTRE TRUEBA, Miguel Angel ; OSTAP, Oleg</creatorcontrib><description>A method of training a machine learning model includes training a primary part of a composite neural network to identify a primary segment of objects in a training image, freezing the primary part of the composite neural network after training the primary part of the composite neural network, and after freezing the primary part of the composite neural network, training, using activations of the primary part of the composite neural network, a secondary part of the composite neural network to identify a first subsegment of objects or a feature of the first subsegment of objects in the training image. The first subsegment of objects is a subset of the primary segment of objects.</description><language>eng</language><subject>CALCULATING ; COMPUTING ; COUNTING ; PHYSICS</subject><creationdate>2024</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&amp;date=20240523&amp;DB=EPODOC&amp;CC=US&amp;NR=2024169698A1$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,776,881,25542,76290</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&amp;date=20240523&amp;DB=EPODOC&amp;CC=US&amp;NR=2024169698A1$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>PERRY, Kristopher Glenn</creatorcontrib><creatorcontrib>BANSAL, Anurag</creatorcontrib><creatorcontrib>MAESTRE TRUEBA, Miguel Angel</creatorcontrib><creatorcontrib>OSTAP, Oleg</creatorcontrib><title>OBJECT DETECTION USING ARTIFICIAL INTELLIGENCE</title><description>A method of training a machine learning model includes training a primary part of a composite neural network to identify a primary segment of objects in a training image, freezing the primary part of the composite neural network after training the primary part of the composite neural network, and after freezing the primary part of the composite neural network, training, using activations of the primary part of the composite neural network, a secondary part of the composite neural network to identify a first subsegment of objects or a feature of the first subsegment of objects in the training image. The first subsegment of objects is a subset of the primary segment of objects.</description><subject>CALCULATING</subject><subject>COMPUTING</subject><subject>COUNTING</subject><subject>PHYSICS</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2024</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNrjZNDzd_JydQ5RcHENAVKe_n4KocGefu4KjkEhnm6ezp6OPgqefiGuPj6e7q5-zq48DKxpiTnFqbxQmptB2c01xNlDN7UgPz61uCAxOTUvtSQ-NNjIwMjE0MzSzNLC0dCYOFUAfeomzg</recordid><startdate>20240523</startdate><enddate>20240523</enddate><creator>PERRY, Kristopher Glenn</creator><creator>BANSAL, Anurag</creator><creator>MAESTRE TRUEBA, Miguel Angel</creator><creator>OSTAP, Oleg</creator><scope>EVB</scope></search><sort><creationdate>20240523</creationdate><title>OBJECT DETECTION USING ARTIFICIAL INTELLIGENCE</title><author>PERRY, Kristopher Glenn ; BANSAL, Anurag ; MAESTRE TRUEBA, Miguel Angel ; OSTAP, Oleg</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_US2024169698A13</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>eng</language><creationdate>2024</creationdate><topic>CALCULATING</topic><topic>COMPUTING</topic><topic>COUNTING</topic><topic>PHYSICS</topic><toplevel>online_resources</toplevel><creatorcontrib>PERRY, Kristopher Glenn</creatorcontrib><creatorcontrib>BANSAL, Anurag</creatorcontrib><creatorcontrib>MAESTRE TRUEBA, Miguel Angel</creatorcontrib><creatorcontrib>OSTAP, Oleg</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>PERRY, Kristopher Glenn</au><au>BANSAL, Anurag</au><au>MAESTRE TRUEBA, Miguel Angel</au><au>OSTAP, Oleg</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>OBJECT DETECTION USING ARTIFICIAL INTELLIGENCE</title><date>2024-05-23</date><risdate>2024</risdate><abstract>A method of training a machine learning model includes training a primary part of a composite neural network to identify a primary segment of objects in a training image, freezing the primary part of the composite neural network after training the primary part of the composite neural network, and after freezing the primary part of the composite neural network, training, using activations of the primary part of the composite neural network, a secondary part of the composite neural network to identify a first subsegment of objects or a feature of the first subsegment of objects in the training image. The first subsegment of objects is a subset of the primary segment of objects.</abstract><oa>free_for_read</oa></addata></record>
fulltext fulltext_linktorsrc
identifier
ispartof
issn
language eng
recordid cdi_epo_espacenet_US2024169698A1
source esp@cenet
subjects CALCULATING
COMPUTING
COUNTING
PHYSICS
title OBJECT DETECTION USING ARTIFICIAL INTELLIGENCE
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-30T07%3A54%3A22IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-epo_EVB&rft_val_fmt=info:ofi/fmt:kev:mtx:patent&rft.genre=patent&rft.au=PERRY,%20Kristopher%20Glenn&rft.date=2024-05-23&rft_id=info:doi/&rft_dat=%3Cepo_EVB%3EUS2024169698A1%3C/epo_EVB%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rfr_iscdi=true