9786208439552 - Deep Learning in POS Automation: Challenges, Innovations & Trends: Exploring the Impact on Efficiency, Accuracy, and Future Developments de Dai, Xiaoyan (11 resultados)

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PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.

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 Publishing, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu.

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, 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. 68 pp. Englisch.

Condición: New. Print on Demand.

Condición: New. Print on Demand.

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Paperback. Condición: new. Paperback. 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. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

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.

Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware Books on Demand GmbH, Überseering 33, 22297 Hamburg 68 pp. Englisch.