mishra reeta (21 risultati)

Soft cover. Condizione: New. ISBN:9789386385499.

N.A. Condizione: New. ISBN:9789386385505.

Condizione: New.

Condizione: new.

HRD. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

Condizione: New.

Condizione: As New. Unread book in perfect condition.

Condizione: As New. Unread book in perfect condition.

Condizione: NEW.

hardcover. Condizione: New.

Condizione: New.

Condizione: New.

Hardback. Condizione: New. This essential book provides a comprehensive, expert-led guide on how federated learning can revolutionize crop yield, enhance resource management, and ensure a pathway to sustainable food quality and safety. The convergence of artificial intelligence, machine learning, and data science with agriculture and food, provides remarkable opportunities to improve quality, sustainability, and productivity in the agricultural sector. Federated Learning is a promising technology that has emerged at this intersection. In the context of smart agriculture, federated learning holds promise for improving crop yield, resource management, and decision-making. Additionally, federated learning provides greater clarity and understanding in the world of agriculture, encouraging stakeholders to explore and adopt this technology for improved farm management. Readers will find the book: Explores the integration of federated learning, a novel machine learning technique, into the realm of agriculture and food quality enhancement, showcasing the latest advancements;Introduces real-world applications of federated learning in agriculture, and demonstrates the way this technology can transform farming practices, crop monitoring, pest control, and food quality assurance;By bridging the fields of agriculture, machine learning, and food science, it offers a holistic perspective on leveraging technology to address challenges in food production and quality management;Emphasizes the importance of sustainability in agriculture, exploring how federated learning can contribute to more efficient resource utilization, reduced environmental impact, and the overall sustainability of food production systems;Discusses the future directions of smart agriculture and food quality enhancement, envisioning how federated learning and other emerging technologies can continue to shape the industry and address evolving challenges. Audience Agriculture specialists, agricultural engineers, professionals associated with food safety, crop managers, quality assurance professionals, IT professionals, data scientists, and academics working towards improved quality and sustainability in agriculture.

Hardcover. Condizione: Brand New. 400 pages. 6.26x1.22x9.29 inches. In Stock.

Condizione: New. 1st edition NO-PA16APR2015-KAP.

Condizione: New.

Buch. Condizione: Neu. Neuware - This essential book provides a comprehensive, expert-led guide on how federated learning can revolutionize crop yield, enhance resource management, and ensure a pathway to sustainable food quality and safety. The convergence of artificial intelligence, machine learning, and data science with agriculture and food, provides remarkable opportunities to improve quality, sustainability, and productivity in the agricultural sector. Federated Learning is a promising technology that has emerged at this intersection. In the context of smart agriculture, federated learning holds promise for improving crop yield, resource management, and decision-making. Additionally, federated learning provides greater clarity and understanding in the world of agriculture, encouraging stakeholders to explore and adopt this technology for improved farm management. Readers will find the book: - Explores the integration of federated learning, a novel machine learning technique, into the realm of agriculture and food quality enhancement, showcasing the latest advancements;- Introduces real-world applications of federated learning in agriculture, and demonstrates the way this technology can transform farming practices, crop monitoring, pest control, and food quality assurance;- By bridging the fields of agriculture, machine learning, and food science, it offers a holistic perspective on leveraging technology to address challenges in food production and quality management;- Emphasizes the importance of sustainability in agriculture, exploring how federated learning can contribute to more efficient resource utilization, reduced environmental impact, and the overall sustainability of food production systems;- Discusses the future directions of smart agriculture and food quality enhancement, envisioning how federated learning and other emerging technologies can continue to shape the industry and address evolving challenges. Audience Agriculture specialists, agricultural engineers, professionals associated with food safety, crop managers, quality assurance professionals, IT professionals, data scientists, and academics working towards improved quality and sustainability in agriculture.

Condizione: New.

Hardback. Condizione: New. This essential book provides a comprehensive, expert-led guide on how federated learning can revolutionize crop yield, enhance resource management, and ensure a pathway to sustainable food quality and safety. The convergence of artificial intelligence, machine learning, and data science with agriculture and food, provides remarkable opportunities to improve quality, sustainability, and productivity in the agricultural sector. Federated Learning is a promising technology that has emerged at this intersection. In the context of smart agriculture, federated learning holds promise for improving crop yield, resource management, and decision-making. Additionally, federated learning provides greater clarity and understanding in the world of agriculture, encouraging stakeholders to explore and adopt this technology for improved farm management. Readers will find the book: Explores the integration of federated learning, a novel machine learning technique, into the realm of agriculture and food quality enhancement, showcasing the latest advancements;Introduces real-world applications of federated learning in agriculture, and demonstrates the way this technology can transform farming practices, crop monitoring, pest control, and food quality assurance;By bridging the fields of agriculture, machine learning, and food science, it offers a holistic perspective on leveraging technology to address challenges in food production and quality management;Emphasizes the importance of sustainability in agriculture, exploring how federated learning can contribute to more efficient resource utilization, reduced environmental impact, and the overall sustainability of food production systems;Discusses the future directions of smart agriculture and food quality enhancement, envisioning how federated learning and other emerging technologies can continue to shape the industry and address evolving challenges. Audience Agriculture specialists, agricultural engineers, professionals associated with food safety, crop managers, quality assurance professionals, IT professionals, data scientists, and academics working towards improved quality and sustainability in agriculture.

Buch. Condizione: Neu. Federated Learning for Smart Agriculture and Food Quality Enhancement | Padmesh Tripathi (u. a.) | Buch | Einband - fest (Hardcover) | Englisch | 2025 | Wiley | EAN 9781394338696 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu.

Hardcover. Condizione: New. 1st Edition. This volume of proceedings is a collection of research works in six main areas viz. Engineering Materials, Manufacturing Methods, Parametric Optimization, Innovative Design and Analysis, Industrial Engineering, Operations and Management. The chapters published in this volume are research papers selected from International Conference on Advanced Production and Industrial Engineering (ICAPIE 2016), held during 9-10 December 2016, organized by the Department of MPIAE, Delhi Technological University, Delhi, India. These papers demonstrate working procedures for conducting experiments, along with the applications of various techniques. With its coverage and focus, this volume will be immensely useful to scientists and academicians of production and industrial engineering. It will also be useful to research scholars of mechanical, production and industrial engineering. Post- and undergraduate students may also refer this book for their research/project works. (jacket).