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Computer Vision-Based Agriculture Engineering (Paperback)
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Computer Vision-Based Agriculture Engineering (Paperback)
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In recent years, computer vision is a fast-growing technique of
agricultural engineering, especially in quality detection of
agricultural products and food safety testing. It can provide
objective, rapid, non-contact and non-destructive methods by
extracting quantitative information from digital images.
Significant scientific and technological advances have been made in
quality inspection, classification and evaluation of a wide range
of food and agricultural products. Computer Vision-Based
Agriculture Engineering focuses on these advances. The book
contains 25 chapters covering computer vision, image processing,
hyperspectral imaging and other related technologies in peanut
aflatoxin, peanut and corn quality varieties, and carrot and potato
quality, as well as pest and disease detection. Features: Discusses
various detection methods in a variety of agricultural crops Each
chapter includes materials and methods used, results and analysis,
and discussion with conclusions Covers basic theory, technical
methods and engineering cases Provides comprehensive coverage on
methods of variety identification, quality detection and detection
of key indicators of agricultural products safety Presents
information on technology of artificial intelligence including deep
learning and transfer learning Computer Vision-Based Agriculture
Engineering is a summary of the author's work over the past 10
years. Professor Han has presented his most recent research results
in all 25 chapters of this book. This unique work provides
students, engineers and technologists working in research,
development, and operations in agricultural engineering with
critical, comprehensive and readily accessible information. It
applies development of artificial intelligence theory and methods
including depth learning and transfer learning to the field of
agricultural engineering testing.
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