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Diagnosetechniken für (EUS) unter Verwendung von KI und maschinellem Lernen
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ISBN10: 6208707994
ISBN13: 9786208707996
Publisher: Verlag Unser Wissen
Published: Feb 28 2025
Pages: 60
Weight: 0.21
Height: 0.14 Width: 6.00 Depth: 9.00
Language: German
ISBN13: 9786208707996
Publisher: Verlag Unser Wissen
Published: Feb 28 2025
Pages: 60
Weight: 0.21
Height: 0.14 Width: 6.00 Depth: 9.00
Language: German
Das Epizootische Ulkus-Syndrom (EUS) ist eine kritische Krankheit, die Sü wasserfische befällt und durch geschwürige Läsionen und erhöhte Sterblichkeitsraten gekennzeichnet ist und somit Aquakulturunternehmen weltweit schadet. Eine rechtzeitige und genaue Identifizierung ist von entscheidender Bedeutung, um die Ausbreitung des EUS zu stoppen und finanzielle Schäden zu begrenzen. Herkömmliche Verfahren wie die Augeninspektion und die histopathologische Analyse sind in der Regel mühsam, teuer und weisen möglicherweise eine unzureichende Empfindlichkeit auf. Methoden der künstlichen Intelligenz (KI), insbesondere maschinelles Lernen und Deep-Learning-Modelle, bieten effektive Lösungen für eine schnelle und präzise Identifizierung von EUS durch die Analyse von Bildern, Umgebungsdaten und mit dem Ausbruch verbundenen Mustern. Diese Forschungsarbeit untersucht den Einsatz von KI-Methoden für die Erkennung von EUS bei Sü wasserfischen und legt dabei den Schwerpunkt auf Techniken, Modellgenauigkeit und praktische Auswirkungen. Unsere Forschung zeigt, dass AI die EUS-Erkennungsraten erhöht und eine effizientere Krankheitsbekämpfung in der Aquakultur ermöglicht.
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