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Computer vision-based agriculture engineering

Author: Han Zhongzhi
Publisher: New York, NY : CRC Press, Taylor & Francis Group, [2020]
Edition/Format:   eBook : Secondary (senior high) school : EnglishView all editions and formats
Summary:
"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 the book of all 25 chapters. This unique work provides student, engineers and technologists working in research, development, and operations in the agricultural engineering with critical, comprehensive and readily accessible information. The book  Read more...
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Genre/Form: Electronic books
Additional Physical Format: Print version:
Zhongzhi, Han, 1981-
Computer vision-based agriculture engineering
New York, NY : CRC Press, Taylor & Francis Group, [2020]
(DLC) 2019025856
Material Type: Secondary (senior high) school, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Han Zhongzhi
ISBN: 9780429289460 0429289464 9781000691955 1000691950 9781000691788 1000691780 9781000691610 1000691616
OCLC Number: 1107166966
Description: 1 online resource
Contents: PrefaceAuthorChapter 1 Detecting Aflatoxin in Agricultural Products by Hyperspectral Imaging: A ReviewChapter 2 Aflatoxin Detection by Fluorescence Index and Narrowband Spectra Based on Hyperspectral ImagingChapter 3 Application-Driven Key Wavelength Mining Method for Aflatoxin Detection Using Hyperspectral DataChapter 4 Deep Learning-Based Aflatoxin Detection of Hyperspectral DataChapter 5 Pixel-Level Aflatoxin Detection Based on Deep Learning and Hyperspectral ImagingChapter 6 A Method of Detecting Peanut Cultivars and Quality Based on the Appearance Characteristic RecognitionChapter 7 Quality Grade Testing of Peanut Based on Image ProcessingChapter 8 Study on Origin Traceability of Peanut Pods Based on Image RecognitionChapter 9 Study on the Pedigree Clustering of Peanut Pod's Variety Based on Image ProcessingChapter 10 Image Features and DUS Testing Traits for Identification and Pedigree Analysis of Peanut Pod VarietiesChapter 11 Counting Ear Rows in Maize Using Image Processing MethodChapter 12 Single-Seed Precise Sowing of Maize Using Computer SimulationChapter 13 Identifying Maize Surface and Species by Transfer LearningChapter 14 A Carrot Sorting System Using Machine Vision TechniqueChapter 15 A New Automatic Carrot Grading System Based on Computer VisionChapter 16 Identifying Carrot Appearance Quality by Transfer LearningChapter 17 Grading System of Pear's Appearance Quality Based on Computer VisionChapter 18 Study on Defect Extraction of Pears with Rich Spots and Neural Network Grading MethodChapter 19 Food Detection Using Infrared Spectroscopy with k-ICA and k-SVM: Variety, Brand, Origin, and AdulterationChapter 20 Study on Vegetable Seed Electrophoresis Image Classification MethodChapter 21 Identifying the Change Process of a Fresh Pepper by Transfer LearningChapter 22 Identifying the Change Process of Fresh Banana by Transfer LearningChapter 23 Pest Recognition Using Transfer LearningChapter 24 Using Deep Learning for Image-Based Plant Disease DetectionChapter 25 Research on the Behavior Trajectory of Ornamental Fish Based on Computer VisionIndex
Responsibility: Han Zhongzhi.

Abstract:

"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 the book of all 25 chapters. This unique work provides student, engineers and technologists working in research, development, and operations in the agricultural engineering with critical, comprehensive and readily accessible information. The book 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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