Zebra fish morphological scoring method based on DeepLabV3Plus
The invention relates to a zebra fish morphological scoring method based on DeepLabV3Plus, is applied to the field of zebra fish morphological scoring, and aims at solving the problems that an existing zebra fish morphological observation method is very time-consuming and indefinite in evaluation st...
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creator | WANG NAN LIANG JINGYU JIANG YUE DONG GONGQING LIN SIJIE |
description | The invention relates to a zebra fish morphological scoring method based on DeepLabV3Plus, is applied to the field of zebra fish morphological scoring, and aims at solving the problems that an existing zebra fish morphological observation method is very time-consuming and indefinite in evaluation standard, the method comprises the following steps: firstly, obtaining zebra fish juvenile fish malformation phenotype image data; openCV is used for data amplification, a DeepLabV3Plus semantic segmentation network is built to train a data set, and a trained model is used for recognition and morphological scoring of zebra fish juvenile fish malformation images. Compared with the prior art, the method can achieve the quick recognition and segmentation of the zebra fish juvenile fish malformation image, completes the automatic evaluation and analysis of the zebra fish juvenile fish morphology, can effectively save the time cost, helps to reduce the subjective judgment error of researchers, and is high in practicality, |
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Compared with the prior art, the method can achieve the quick recognition and segmentation of the zebra fish juvenile fish malformation image, completes the automatic evaluation and analysis of the zebra fish juvenile fish morphology, can effectively save the time cost, helps to reduce the subjective judgment error of researchers, and is high in practicality,</description><subject>CALCULATING</subject><subject>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</subject><subject>COMPUTING</subject><subject>COUNTING</subject><subject>HANDLING RECORD CARRIERS</subject><subject>PHYSICS</subject><subject>PRESENTATION OF DATA</subject><subject>RECOGNITION OF DATA</subject><subject>RECORD CARRIERS</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2021</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNrjZLCLSk0qSlRIyyzOUMjNLyrIyM_JT89MTsxRKE7OL8rMS1fITS3JyE9RSEosTk1RyM9TcElNLfBJTAozDsgpLeZhYE1LzClO5YXS3AyKbq4hzh66qQX58anFBYnJqXmpJfHOfoaGxsZmhsamxo7GxKgBADFpMBM</recordid><startdate>20210907</startdate><enddate>20210907</enddate><creator>WANG NAN</creator><creator>LIANG JINGYU</creator><creator>JIANG YUE</creator><creator>DONG GONGQING</creator><creator>LIN SIJIE</creator><scope>EVB</scope></search><sort><creationdate>20210907</creationdate><title>Zebra fish morphological scoring method based on DeepLabV3Plus</title><author>WANG NAN ; LIANG JINGYU ; JIANG YUE ; DONG GONGQING ; LIN SIJIE</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_CN113361353A3</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>chi ; eng</language><creationdate>2021</creationdate><topic>CALCULATING</topic><topic>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</topic><topic>COMPUTING</topic><topic>COUNTING</topic><topic>HANDLING RECORD CARRIERS</topic><topic>PHYSICS</topic><topic>PRESENTATION OF DATA</topic><topic>RECOGNITION OF DATA</topic><topic>RECORD CARRIERS</topic><toplevel>online_resources</toplevel><creatorcontrib>WANG NAN</creatorcontrib><creatorcontrib>LIANG JINGYU</creatorcontrib><creatorcontrib>JIANG YUE</creatorcontrib><creatorcontrib>DONG GONGQING</creatorcontrib><creatorcontrib>LIN SIJIE</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>WANG NAN</au><au>LIANG JINGYU</au><au>JIANG YUE</au><au>DONG GONGQING</au><au>LIN SIJIE</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>Zebra fish morphological scoring method based on DeepLabV3Plus</title><date>2021-09-07</date><risdate>2021</risdate><abstract>The invention relates to a zebra fish morphological scoring method based on DeepLabV3Plus, is applied to the field of zebra fish morphological scoring, and aims at solving the problems that an existing zebra fish morphological observation method is very time-consuming and indefinite in evaluation standard, the method comprises the following steps: firstly, obtaining zebra fish juvenile fish malformation phenotype image data; openCV is used for data amplification, a DeepLabV3Plus semantic segmentation network is built to train a data set, and a trained model is used for recognition and morphological scoring of zebra fish juvenile fish malformation images. Compared with the prior art, the method can achieve the quick recognition and segmentation of the zebra fish juvenile fish malformation image, completes the automatic evaluation and analysis of the zebra fish juvenile fish morphology, can effectively save the time cost, helps to reduce the subjective judgment error of researchers, and is high in practicality,</abstract><oa>free_for_read</oa></addata></record> |
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subjects | CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING HANDLING RECORD CARRIERS PHYSICS PRESENTATION OF DATA RECOGNITION OF DATA RECORD CARRIERS |
title | Zebra fish morphological scoring method based on DeepLabV3Plus |
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