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Intelligent image analysis for plant phenotyping /
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
Intelligent image analysis for plant phenotyping // edited by Ashok Samal and Sruti Das Choudhury.
其他作者:
Samal, Ashok.
出版者:
Boca Raton, FL :CRC Press, : c2021.,
面頁冊數:
xix, 326 p. :ill. ; : 24 cm.;
標題:
Image processing - Digital techniques. -
ISBN:
9781138038554 :
Intelligent image analysis for plant phenotyping /
Intelligent image analysis for plant phenotyping /
edited by Ashok Samal and Sruti Das Choudhury. - 1st ed. - Boca Raton, FL :CRC Press,c2021. - xix, 326 p. :ill. ;24 cm.
Includes bibliographical references and index.
Image-Based Plant Phenotyping: Opportunities and Challenges -- Multi-Sensor Phenotyping for Crop Physiology -- Image Processing Techniques for Plant Phenotyping -- Segmentation Techniques and Challenges in Plant Phenotyping -- Structural High Throughput Plant Phenotyping based on Image Sequence Analysis -- Geometry Reconstruction of Plants -- Image-Based Structural Phenotyping of Stems and Branches -- Time Series and Eigen Value Based Analysis of Plant Phenotypes -- Data-Driven Techniques for Plant Phenotyping Using Hyperspectral Imagery -- Machine Learning and Statistical Approaches for Plant Phenotyping -- A Brief Introduction to Machine Learning and Deep Learning for Computer Vision -- Chlorophyll a Fluorescence Analyses to Investigate the Impacts of Genotype, Species, and Stress on Photosynthetic Efficiency and Plant Productivity -- Predicting Yield by Modeling Interactions between Canopy Coverage Image Data, Genotypic and Environmental Information for Soybeans -- Field Phenotyping for Salt Tolerance and Imaging Techniques for Crop Stress Biology -- The Adoption of Automated Phenotyping by Plant Breeders.
"Domesticated crops are the result of artificial selection for particular phenotypes and, in some case, natural selection for an adaptive trait. Intelligent Image Analysis for Plant Phenotyping reviews information on time-saving techniques using computer vision and imaging technologies. These methodologies provide an automated, non-invasive and scalable mechanism to define and collect plant phenotypes. Beautifully illustrated with numerous color images, this book is invaluable for those working in the emerging fields at the intersection of computer vision and plant sciences"--
ISBN: 9781138038554 :NT5642
LCCN: 2020020511Subjects--Topical Terms:
555959
Image processing
--Digital techniques.
LC Class. No.: TA1637 / .I475 2021
Dewey Class. No.: 576.5/30285642
National Agricultural Library Call No.: TA1637 / .I584 2021
Intelligent image analysis for plant phenotyping /
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Image-Based Plant Phenotyping: Opportunities and Challenges -- Multi-Sensor Phenotyping for Crop Physiology -- Image Processing Techniques for Plant Phenotyping -- Segmentation Techniques and Challenges in Plant Phenotyping -- Structural High Throughput Plant Phenotyping based on Image Sequence Analysis -- Geometry Reconstruction of Plants -- Image-Based Structural Phenotyping of Stems and Branches -- Time Series and Eigen Value Based Analysis of Plant Phenotypes -- Data-Driven Techniques for Plant Phenotyping Using Hyperspectral Imagery -- Machine Learning and Statistical Approaches for Plant Phenotyping -- A Brief Introduction to Machine Learning and Deep Learning for Computer Vision -- Chlorophyll a Fluorescence Analyses to Investigate the Impacts of Genotype, Species, and Stress on Photosynthetic Efficiency and Plant Productivity -- Predicting Yield by Modeling Interactions between Canopy Coverage Image Data, Genotypic and Environmental Information for Soybeans -- Field Phenotyping for Salt Tolerance and Imaging Techniques for Crop Stress Biology -- The Adoption of Automated Phenotyping by Plant Breeders.
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"Domesticated crops are the result of artificial selection for particular phenotypes and, in some case, natural selection for an adaptive trait. Intelligent Image Analysis for Plant Phenotyping reviews information on time-saving techniques using computer vision and imaging technologies. These methodologies provide an automated, non-invasive and scalable mechanism to define and collect plant phenotypes. Beautifully illustrated with numerous color images, this book is invaluable for those working in the emerging fields at the intersection of computer vision and plant sciences"--
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