{"id":23671,"date":"2024-03-28T14:14:57","date_gmt":"2024-03-28T18:14:57","guid":{"rendered":"https:\/\/clemex.com\/?p=23671"},"modified":"2024-08-08T09:01:10","modified_gmt":"2024-08-08T13:01:10","slug":"image-analysis-using-clemex-studios-artificial-intelligence","status":"publish","type":"post","link":"https:\/\/clemex.com\/image-analysis-using-clemex-studios-artificial-intelligence\/","title":{"rendered":"Image analysis using Clemex Studio\u2019s artificial intelligence"},"content":{"rendered":"\t\t
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\n\t\t\t\t\t\tHome<\/a><\/span><\/span>\t\t\t\t\t<\/div> \n\t\t\t\t<\/div> \n\t\t\t<\/div> \n\t\t<\/div>\n\t\t

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By Francis Quintal Lauzon<\/span>, Director of Products and Innovation and Nicolas Dion, Ing.<\/span><\/p>\n

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Introduction<\/span><\/span><\/strong><\/span><\/h3>\n

Recent advances in artificial intelligence have given the possibility for image analysis to be simplified. One specific area of image analysis where artificial intelligence performs particularly well is called image segmentation. Image segmentation is the process of partitioning an image into classes. An example of this is segmentation of a delta-ferrite alloy metallograph into its primary and delta-ferrite phase as shown below in Figure 1.<\/p>\n

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Figure 1. <\/span><\/span><\/strong>Segmentation of a delta-ferrite alloy micrograph<\/span><\/span><\/span><\/p>\n

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