Deep Learning Plant Science (16 results)

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

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Hardcover. Condition: Brand New. 376 pages. 9.61x6.77x0.59 inches. In Stock.

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Buch. Condition: Neu. Neuware - This book introduces the fundamentals of deep learning models and their current applications in a diverse range of subtopics in plant sciences and agriculture.Areas covered include: functional genomics, multiple omics, stress physiology, plant disease diagnosis, plant-microbe interactions, and high-throughput technologies (phenotyping and synthetic biology).Deep-learning models are also being used in developing pest and weed control strategies, the use of unmanned aerial vehicles in agriculture, greenhouse management and strategies for stress-smart and sustainable precision agriculture.This book offers an ideal reference for readers in a range of research fields in plant biology, plant pathology, and agricultural crop sciences. It is designed to be an inspiration for new ideas and future experiments to advance the progress of stress-smart and sustainable agriculture. …

Hardcover. Condition: new. Hardcover. This book introduces the fundamentals of deep learning models and their current applications in a diverse range of subtopics in plant sciences and agriculture. Areas covered include: functional genomics, multiple omics, stress physiology, plant disease diagnosis, plant-microbe interactions, and high-throughput technologies (phenotyping and synthetic biology). Deep-learning models are also being used in developing pest and weed control strategies, the use of unmanned aerial vehicles in agriculture, greenhouse management and strategies for stress-smart and sustainable precision agriculture. This book offers an ideal reference for readers in a range of research fields in plant biology, plant pathology, and agricultural crop sciences. It is designed to be an inspiration for new ideas and future experiments to advance the progress of stress-smart and sustainable agriculture. This wide-ranging book introduces the fundamentals of deep learning models and their current applications across a diversity of topics in agricultural biotechnology, crop science and plant biology. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Hardcover. Condition: Brand New. 376 pages. 9.61x6.77x0.59 inches. In Stock. This item is printed on demand.

Hardcover. Condition: new. Hardcover. This book introduces the fundamentals of deep learning models and their current applications in a diverse range of subtopics in plant sciences and agriculture. Areas covered include: functional genomics, multiple omics, stress physiology, plant disease diagnosis, plant-microbe interactions, and high-throughput technologies (phenotyping and synthetic biology). Deep-learning models are also being used in developing pest and weed control strategies, the use of unmanned aerial vehicles in agriculture, greenhouse management and strategies for stress-smart and sustainable precision agriculture. This book offers an ideal reference for readers in a range of research fields in plant biology, plant pathology, and agricultural crop sciences. It is designed to be an inspiration for new ideas and future experiments to advance the progress of stress-smart and sustainable agriculture. This wide-ranging book introduces the fundamentals of deep learning models and their current applications across a diversity of topics in agricultural biotechnology, crop science and plant biology. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…