9786208439552 - deep learning in pos automation: challenges, innovations & trends: exploring the impact on efficiency, accuracy, and future developments de dai, xiaoyan (10 resultados)
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Taschenbuch. Condición: Neu. Deep Learning in POS Automation: Challenges, Innovations & Trends | Exploring the Impact on Efficiency, Accuracy, and Future Developments | Xiaoyan Dai | Taschenbuch | Englisch | 2025 | LAP LAMBERT Academic Publishing | EAN 9786208439552 | Verantwortliche Person für die EU: SIA OmniScriptum Publishin…g, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu.
Idioma: Inglés
Editorial: Omniscriptum, LAP Lambert Academic Publishing, 2025
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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Deep learning has revolutionized computer vision, driving automation in industries like retail. Artificial Intelligence (AI) powered object recognition is transforming Point-of-Sale (POS) automation, improving transaction speed, acc…uracy, and efficiency. However, challenges remain, such as barcode recognition in difficult conditions and optimizing AI models for real-time performance.This book explores how deep learning enhances POS automation, focusing on barcode recognition and discount sale identification. It covers the evolution of POS systems, AI's role in retail, and advanced barcode detection techniques, including deep learning models and synthetic-to-real data augmentation. The book also discusses AI-driven discount sale recognition, system design, and experimental results.Beyond technical solutions, the book addresses deployment challenges, such as hardware integration, balancing cloud and edge AI processing, and optimizing models for real-time use. It also looks at emerging trends like self-supervised learning, domain adaptation, and applications in logistics and automated warehouses. 68 pp. Englisch.
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Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Deep learning has revolutionized computer vision, driving automation in industries like retail. Artificial Intelligence (AI) powered object recognition is transforming Point-of-Sale (POS) automation, improving transaction speed, accurac…y, and efficiency. However, challenges remain, such as barcode recognition in difficult conditions and optimizing AI models for real-time performance.This book explores how deep learning enhances POS automation, focusing on barcode recognition and discount sale identification. It covers the evolution of POS systems, AI's role in retail, and advanced barcode detection techniques, including deep learning models and synthetic-to-real data augmentation. The book also discusses AI-driven discount sale recognition, system design, and experimental results.Beyond technical solutions, the book addresses deployment challenges, such as hardware integration, balancing cloud and edge AI processing, and optimizing models for real-time use. It also looks at emerging trends like self-supervised learning, domain adaptation, and applications in logistics and automated warehouses.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 68 pp. Englisch.
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Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH
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Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Deep learning has revolutionized computer vision, driving automation in industries like retail. Artificial Intelligence (AI) powered object recognition is transforming Point-of-Sale (POS) automation, improving transaction speed, accuracy…, and efficiency. However, challenges remain, such as barcode recognition in difficult conditions and optimizing AI models for real-time performance.This book explores how deep learning enhances POS automation, focusing on barcode recognition and discount sale identification. It covers the evolution of POS systems, AI's role in retail, and advanced barcode detection techniques, including deep learning models and synthetic-to-real data augmentation. The book also discusses AI-driven discount sale recognition, system design, and experimental results.Beyond technical solutions, the book addresses deployment challenges, such as hardware integration, balancing cloud and edge AI processing, and optimizing models for real-time use. It also looks at emerging trends like self-supervised learning, domain adaptation, and applications in logistics and automated warehouses.
