{"id":3047,"date":"2022-07-13T09:30:00","date_gmt":"2022-07-13T07:30:00","guid":{"rendered":"https:\/\/cirpicme.org\/?page_id=3047"},"modified":"2022-07-26T13:05:43","modified_gmt":"2022-07-26T11:05:43","slug":"feature-based-optical-surface-quality-measure-within-cyber-physical-learning-factory","status":"publish","type":"page","link":"https:\/\/cirpicme.org\/index.php\/feature-based-optical-surface-quality-measure-within-cyber-physical-learning-factory\/","title":{"rendered":"Feature-based optical surface quality measure within cyber-physical learning factory"},"content":{"rendered":"\n<p class=\"wp-block-paragraph\"><em>by Tamal Ghosh (Norway)<\/em><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Abstract<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">This article presents a computer vision-based module to inspect the surface quality of products inside a cyber-physical (CP) learning factory. The proposed system can capture the images of the product surface and store them within a locally attached portable computer. These images are then analyzed using deep learning (DL) technique which defines the correlations among the image features and product quality measure values recorded using mechanical device. This analysis further identifies the nature of the features and portrays the way these features could be used as standalone product surface quality measures.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Keywords<\/strong>: Product Quality; Cyber-Physical Learning Factory; Feature Extraction; Optical Image Analysis<\/p>\n\n\n\n<div style=\"height:20px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Video presentation<\/strong><\/p>\n\n\n\n<figure class=\"wp-block-video\"><video height=\"720\" style=\"aspect-ratio: 1280 \/ 720;\" width=\"1280\" controls src=\"https:\/\/cirpicme.org\/wp-content\/uploads\/2020\/06\/CIRPe2016_Caggiano.mp4\"><\/video><\/figure>\n\n\n\n<p class=\"wp-block-paragraph\"><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Presenting author<\/strong><\/p>\n\n\n\n<figure class=\"wp-block-table is-style-stripes\"><table class=\"has-background\" style=\"background-color:#f3f4f5\"><tbody><tr><td><\/td><td><\/td><td><\/td><\/tr><tr><td><img data-recalc-dims=\"1\" loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"150\" class=\"wp-image-2726\" style=\"width: 150px;\" src=\"https:\/\/i0.wp.com\/cirpicme.org\/wp-content\/uploads\/2022\/06\/IMG_3323_2-edited-1.jpg?resize=150%2C150&#038;ssl=1\" alt=\"\" srcset=\"https:\/\/i0.wp.com\/cirpicme.org\/wp-content\/uploads\/2022\/06\/IMG_3323_2-edited-1.jpg?w=954&amp;ssl=1 954w, https:\/\/i0.wp.com\/cirpicme.org\/wp-content\/uploads\/2022\/06\/IMG_3323_2-edited-1.jpg?resize=300%2C300&amp;ssl=1 300w, https:\/\/i0.wp.com\/cirpicme.org\/wp-content\/uploads\/2022\/06\/IMG_3323_2-edited-1.jpg?resize=150%2C150&amp;ssl=1 150w, https:\/\/i0.wp.com\/cirpicme.org\/wp-content\/uploads\/2022\/06\/IMG_3323_2-edited-1.jpg?resize=768%2C769&amp;ssl=1 768w\" sizes=\"auto, (max-width: 150px) 100vw, 150px\" \/><\/td><td><strong>Name:<\/strong><br><br><strong>Affiliation:<\/strong><br><br><strong>Email:<\/strong><\/td><td>Tamal Ghosh<br><br>Norwegian University of Science and Technology, Norway<br><br>tamal.ghosh@ntnu.no<\/td><\/tr><tr><td><\/td><td><\/td><td><\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<p class=\"wp-block-paragraph\"><\/p>\n","protected":false},"excerpt":{"rendered":"<p>by Tamal Ghosh (Norway) Abstract This article presents a computer vision-based module to inspect the surface quality of products inside a cyber-physical (CP) learning factory. The proposed system can capture the images of the product surface and store them within a locally attached portable computer. These images are then analyzed&#8230;<\/p>\n<p> <a class=\"continue-reading-link\" href=\"https:\/\/cirpicme.org\/index.php\/feature-based-optical-surface-quality-measure-within-cyber-physical-learning-factory\/\"><span>Continue reading<\/span><i class=\"crycon-right-dir\"><\/i><\/a> <\/p>\n","protected":false},"author":9,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"open","ping_status":"closed","template":"","meta":{"nf_dc_page":"","om_disable_all_campaigns":false,"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"footnotes":""},"class_list":["post-3047","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/cirpicme.org\/index.php\/wp-json\/wp\/v2\/pages\/3047","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/cirpicme.org\/index.php\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/cirpicme.org\/index.php\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/cirpicme.org\/index.php\/wp-json\/wp\/v2\/users\/9"}],"replies":[{"embeddable":true,"href":"https:\/\/cirpicme.org\/index.php\/wp-json\/wp\/v2\/comments?post=3047"}],"version-history":[{"count":1,"href":"https:\/\/cirpicme.org\/index.php\/wp-json\/wp\/v2\/pages\/3047\/revisions"}],"predecessor-version":[{"id":3050,"href":"https:\/\/cirpicme.org\/index.php\/wp-json\/wp\/v2\/pages\/3047\/revisions\/3050"}],"wp:attachment":[{"href":"https:\/\/cirpicme.org\/index.php\/wp-json\/wp\/v2\/media?parent=3047"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}