{"id":7178,"date":"2025-04-03T14:02:03","date_gmt":"2025-04-03T12:02:03","guid":{"rendered":"https:\/\/rcai.de\/?p=7178"},"modified":"2025-04-03T14:07:06","modified_gmt":"2025-04-03T12:07:06","slug":"spri","status":"publish","type":"post","link":"https:\/\/rcai.de\/en\/2025\/04\/03\/spri\/","title":{"rendered":"ML for SPRi"},"content":{"rendered":"

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Symbol image (Midjourney, Generative AI)<\/figcaption><\/figure>\n<\/div>\n\n\n\n
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Machine learning for Surface Plasmon Resonance imaging (SPRi)<\/h4>\n\n\n\n
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Project responsible: Prof. Dr. Rudolf Bierl<\/a><\/h6>\n\n\n\n
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Duration: since 2024<\/h6>\n<\/div>\n<\/div>\n\n\n\n
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Neue, KI-unterst\u00fczte Sensing-Methoden<\/h4>\n\n\n\n
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Im Projekt wird maschinelles Lernen auf verschiedene Weise eingesetzt, um die analytische Leistung eines Oberfl\u00e4chenplasmonenresonanzsensors zu verbessern. Die Oberfl\u00e4chenplasmonenresonanz-Bildgebung (SPRi) liefert hochdimensionale Daten mit hoher Empfindlichkeit gegen\u00fcber der Oberfl\u00e4che.<\/h6>\n\n\n\n

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Ein Ziel des Vorhabens ist die Erm\u00f6glichung einer spezifischen Signalverarbeitung f\u00fcr eine SPRi-Konfiguration, die divergentes Licht verwendet, um die Oberfl\u00e4chenplasmonenresonanzbedingungen \u00fcber die Oberfl\u00e4che hinweg zu ver\u00e4ndern. Es wird untersucht, wie diese Informationen in einem analytischen Kontext f\u00fcr die Sensorcharakterisierung und -entwicklung genutzt werden k\u00f6nnen, um neue Sensing-Methoden zu erm\u00f6glichen.<\/h6>\n\n\n\n

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Dar\u00fcber hinaus wird evaluiert, wie Deep Learning eingesetzt werden kann, um bei der Erkennung kleiner Molek\u00fcle mithilfe des SPRi-Sensors und unspezifischer Rezeptorelemente zu unterst\u00fctzten.<\/h6>\n<\/div>","protected":false},"excerpt":{"rendered":"

Machine learning to improve the analytical performance of an SPRi sensor<\/p>","protected":false},"author":8,"featured_media":7179,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"cybocfi_hide_featured_image":"","footnotes":""},"categories":[71,41,73],"tags":[],"class_list":["post-7178","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-projects","category-sappz","category-enabling-technologies"],"_links":{"self":[{"href":"https:\/\/rcai.de\/en\/wp-json\/wp\/v2\/posts\/7178","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/rcai.de\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/rcai.de\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/rcai.de\/en\/wp-json\/wp\/v2\/users\/8"}],"replies":[{"embeddable":true,"href":"https:\/\/rcai.de\/en\/wp-json\/wp\/v2\/comments?post=7178"}],"version-history":[{"count":3,"href":"https:\/\/rcai.de\/en\/wp-json\/wp\/v2\/posts\/7178\/revisions"}],"predecessor-version":[{"id":7183,"href":"https:\/\/rcai.de\/en\/wp-json\/wp\/v2\/posts\/7178\/revisions\/7183"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/rcai.de\/en\/wp-json\/wp\/v2\/media\/7179"}],"wp:attachment":[{"href":"https:\/\/rcai.de\/en\/wp-json\/wp\/v2\/media?parent=7178"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/rcai.de\/en\/wp-json\/wp\/v2\/categories?post=7178"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/rcai.de\/en\/wp-json\/wp\/v2\/tags?post=7178"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}