Defect detection method, electronic equipment and storage medium
The invention relates to the technical field of flaw detection, and provides a flaw detection method, electronic equipment and a storage medium. The flaw detection method comprises the following steps: inputting a target image into a pre-trained first classification model to obtain a first classific...
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creator | LIN ZECHENG WU YANGZHEN |
description | The invention relates to the technical field of flaw detection, and provides a flaw detection method, electronic equipment and a storage medium. The flaw detection method comprises the following steps: inputting a target image into a pre-trained first classification model to obtain a first classification result; under the condition that the first classification result indicates that no flaw exists in the target image, inputting the target image into a flaw segmentation model to obtain a segmentation result; the first classification model is used for identifying flaw types in the input image. The defect detection method can solve the problem that the defect detection result is inaccurate, because the first classification model only needs to detect the defect type in the target image, the defect area does not need to be marked in the training process of the first classification model, and the defect detection efficiency is improved under the condition that the first classification model does not detect the defe |
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The flaw detection method comprises the following steps: inputting a target image into a pre-trained first classification model to obtain a first classification result; under the condition that the first classification result indicates that no flaw exists in the target image, inputting the target image into a flaw segmentation model to obtain a segmentation result; the first classification model is used for identifying flaw types in the input image. The defect detection method can solve the problem that the defect detection result is inaccurate, because the first classification model only needs to detect the defect type in the target image, the defect area does not need to be marked in the training process of the first classification model, and the defect detection efficiency is improved under the condition that the first classification model does not detect the defe</description><language>chi ; eng</language><subject>CALCULATING ; COMPUTING ; COUNTING ; IMAGE DATA PROCESSING OR GENERATION, IN GENERAL ; PHYSICS</subject><creationdate>2023</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=20230811&DB=EPODOC&CC=CN&NR=116579986A$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,780,885,25564,76547</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20230811&DB=EPODOC&CC=CN&NR=116579986A$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>LIN ZECHENG</creatorcontrib><creatorcontrib>WU YANGZHEN</creatorcontrib><title>Defect detection method, electronic equipment and storage medium</title><description>The invention relates to the technical field of flaw detection, and provides a flaw detection method, electronic equipment and a storage medium. The flaw detection method comprises the following steps: inputting a target image into a pre-trained first classification model to obtain a first classification result; under the condition that the first classification result indicates that no flaw exists in the target image, inputting the target image into a flaw segmentation model to obtain a segmentation result; the first classification model is used for identifying flaw types in the input image. The defect detection method can solve the problem that the defect detection result is inaccurate, because the first classification model only needs to detect the defect type in the target image, the defect area does not need to be marked in the training process of the first classification model, and the defect detection efficiency is improved under the condition that the first classification model does not detect the defe</description><subject>CALCULATING</subject><subject>COMPUTING</subject><subject>COUNTING</subject><subject>IMAGE DATA PROCESSING OR GENERATION, IN GENERAL</subject><subject>PHYSICS</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2023</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNrjZHBwSU1LTS5RSEktAVKZ-XkKuaklGfkpOgqpOUCBovy8zGSF1MLSzILc1LwShcS8FIXikvyixPRUoMKUzNJcHgbWtMSc4lReKM3NoOjmGuLsoZtakB-fWlyQmJyal1oS7-xnaGhmam5paWHmaEyMGgDXZDGP</recordid><startdate>20230811</startdate><enddate>20230811</enddate><creator>LIN ZECHENG</creator><creator>WU YANGZHEN</creator><scope>EVB</scope></search><sort><creationdate>20230811</creationdate><title>Defect detection method, electronic equipment and storage medium</title><author>LIN ZECHENG ; WU YANGZHEN</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_CN116579986A3</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>chi ; eng</language><creationdate>2023</creationdate><topic>CALCULATING</topic><topic>COMPUTING</topic><topic>COUNTING</topic><topic>IMAGE DATA PROCESSING OR GENERATION, IN GENERAL</topic><topic>PHYSICS</topic><toplevel>online_resources</toplevel><creatorcontrib>LIN ZECHENG</creatorcontrib><creatorcontrib>WU YANGZHEN</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>LIN ZECHENG</au><au>WU YANGZHEN</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>Defect detection method, electronic equipment and storage medium</title><date>2023-08-11</date><risdate>2023</risdate><abstract>The invention relates to the technical field of flaw detection, and provides a flaw detection method, electronic equipment and a storage medium. The flaw detection method comprises the following steps: inputting a target image into a pre-trained first classification model to obtain a first classification result; under the condition that the first classification result indicates that no flaw exists in the target image, inputting the target image into a flaw segmentation model to obtain a segmentation result; the first classification model is used for identifying flaw types in the input image. The defect detection method can solve the problem that the defect detection result is inaccurate, because the first classification model only needs to detect the defect type in the target image, the defect area does not need to be marked in the training process of the first classification model, and the defect detection efficiency is improved under the condition that the first classification model does not detect the defe</abstract><oa>free_for_read</oa></addata></record> |
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language | chi ; eng |
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subjects | CALCULATING COMPUTING COUNTING IMAGE DATA PROCESSING OR GENERATION, IN GENERAL PHYSICS |
title | Defect detection method, electronic equipment and storage medium |
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