Monochrome images with their grayscale representation devoid of color have played a significant role in various aspects of artificial intelligence (AI), particularly in the field of computer vision. This topic explores the significance and potential benefits of monochrome images in enhancing object recognition algorithms used in AI systems. The aim is to investigate the impact of monochrome images on the accuracy and efficiency of object recognition tasks performed by AI models, without relying on plagiarized content. The book examines the historical background of monochrome images in computer vision, the underlying principles of object recognition in AI, and how monochrome images can be utilized to improve this process. Various approaches, techniques, and datasets utilized in monochrome image-based object recognition are discussed, along with their advantages and limitations.
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Sima Das. Departament komp'üternyh nauk i inzhenerii. Bengal'skij inzhenerno-tehnologicheskij kolledzh, Bidhannagar, Durgapur, Zapadnaq Bengaliq, Indiq.Shantanu Sengupta.Samik Acharq. Departament prikladnoj statistiki i analitiki, Institut issledowanij menedzhmenta, Kal'kutta, Zapadnaq Bengaliq, Indiq.
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Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Monochrome images with their grayscale representation devoid of color have played a significant role in various aspects of artificial intelligence (AI), particularly in the field of computer vision. This topic explores the significance and potential benefit. Bestandsnummer des Verkäufers 1269270020
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Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Monochrome images with their grayscale representation devoid of color have played a significant role in various aspects of artificial intelligence (AI), particularly in the field of computer vision. This topic explores the significance and potential benefits of monochrome images in enhancing object recognition algorithms used in AI systems. The aim is to investigate the impact of monochrome images on the accuracy and efficiency of object recognition tasks performed by AI models, without relying on plagiarized content. The book examines the historical background of monochrome images in computer vision, the underlying principles of object recognition in AI, and how monochrome images can be utilized to improve this process. Various approaches, techniques, and datasets utilized in monochrome image-based object recognition are discussed, along with their advantages and limitations.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 116 pp. Englisch. Bestandsnummer des Verkäufers 9786206844662
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Taschenbuch. Zustand: Neu. Monochrome Images for Enhancing Object Recognition | By Using Artificial Intelligence Techniques | Sima Das (u. a.) | Taschenbuch | Englisch | 2023 | LAP LAMBERT Academic Publishing | EAN 9786206844662 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Bestandsnummer des Verkäufers 128072877
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Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Monochrome images with their grayscale representation devoid of color have played a significant role in various aspects of artificial intelligence (AI), particularly in the field of computer vision. This topic explores the significance and potential benefits of monochrome images in enhancing object recognition algorithms used in AI systems. The aim is to investigate the impact of monochrome images on the accuracy and efficiency of object recognition tasks performed by AI models, without relying on plagiarized content. The book examines the historical background of monochrome images in computer vision, the underlying principles of object recognition in AI, and how monochrome images can be utilized to improve this process. Various approaches, techniques, and datasets utilized in monochrome image-based object recognition are discussed, along with their advantages and limitations. Bestandsnummer des Verkäufers 9786206844662
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