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Computer Vision-Based Agriculture Engineering (Record no. 582)

MARC details
000 -LEADER
fixed length control field 02601 a2200301 4500
001 - CONTROL NUMBER
control field 1032089210
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20250317100355.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 250312042021xx 162 eng
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781032089218
037 ## - SOURCE OF ACQUISITION
Source of stock number/acquisition Taylor & Francis
Terms of availability GBP 46.99
Form of issue BB
040 ## - CATALOGING SOURCE
Original cataloging agency 01
041 ## - LANGUAGE CODE
Language code of text/sound track or separate title eng
072 7# - SUBJECT CATEGORY CODE
Subject category code TVB
Source thema
072 7# - SUBJECT CATEGORY CODE
Subject category code RGC
Source thema
072 7# - SUBJECT CATEGORY CODE
Subject category code TVB
Source bic
072 7# - SUBJECT CATEGORY CODE
Subject category code RGC
Source bic
072 7# - SUBJECT CATEGORY CODE
Subject category code TEC036000
Source bisac
072 7# - SUBJECT CATEGORY CODE
Subject category code SCI011000
Source bisac
072 7# - SUBJECT CATEGORY CODE
Subject category code SCI086000
Source bisac
072 7# - SUBJECT CATEGORY CODE
Subject category code TEC003000
Source bisac
072 7# - SUBJECT CATEGORY CODE
Subject category code 631.5233
Source bisac
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Han Zhongzhi
245 10 - TITLE STATEMENT
Title Computer Vision-Based Agriculture Engineering
250 ## - EDITION STATEMENT
Edition statement 1
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Name of publisher, distributor, etc. CRC Press
Date of publication, distribution, etc. 20210630
300 ## - PHYSICAL DESCRIPTION
Extent 348 p
520 ## - SUMMARY, ETC.
Expansion of summary note 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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