Intelligent Image Analysis for Plant Phenotyping

Herausgeber: Das Choudhury, Sruti; Samal, Ashok

• Gebundenes Buch

Produktbeschreibung

Intelligent Image Analysis for Plant Phenotyping reviews information on time-saving techniques for identifying plant traits using computer vision and imaging technologies. Beautifully illustrated with numerous color images, this book is written for those working at the intersection of computer vision and plant sciences.

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Produktdetails

• Verlag: CRC Press
• Seitenzahl: 348
• Erscheinungstermin: 22. Oktober 2020
• Englisch
• Abmessung: 240mm x 161mm x 23mm
• Gewicht: 689g
• ISBN-13: 9781138038554
• ISBN-10: 1138038555
• Artikelnr.: 60012138

Autorenporträt

Ashok Samal is a Professor in the Department of Computer Science and Engineering at the University of Nebraska-Lincoln, USA. He received Bachelor of Technology from the Indian Institute of Technology, Kanpur, India, and Ph.D. from the University of Utah, Salt Lake City, USA. His research interests include computer vision and data mining, and he has published extensively in these areas. More recently, he has focused on plant phenotyping and co-leads the Plant Vision Initiative research group at the University of Nebraska-Lincoln. Sruti Das Choudhury is a Research Assistant Professor in the School of Natural Resources at the University of Nebraska-Lincoln, USA. Previously, she was a Postdoctoral Research Associate in the Department of Computer Science and Engineering at the University of Nebraska-Lincoln and an Early Career Research Fellow in the Institute of Advanced Study at the University of Warwick, UK. She received Bachelor of Technology in Information Technology from the West Bengal University of Technology and Master of Technology in Computer Science and Application from the University of Calcutta, India. She obtained her Ph.D. in Computer Science Engineering from the University of Warwick, UK. Her research focus is on biometrics, data science, and most recently, image-based plant phenotyping analysis. She co-leads the Plant Vision Initiative research group at the University of Nebraska-Lincoln.

Inhaltsangabe

PART I Basics Chapter 1 Image-Based Plant Phenotyping: Opportunities and
Challenges Chapter 2 Multisensor Phenotyping for Crop Physiology Chapter 3
Image Processing Techniques for Plant Phenotyping PART II Techniques
Chapter 4 Segmentation Techniques and Challenges in Plant Phenotyping
Chapter 5 Structural High-Throughput Plant Phenotyping Based on Image
Sequence Analysis Chapter 6 Geometry Reconstruction of Plants Chapter 7
Image-Based Structural Phenotyping of Stems and Branches Chapter 8 Time
Series- and Eigenvalue-Based Analysis of Plant Phenotypes Chapter 9
Data-Driven Techniques for Plant Phenotyping Using Hyperspectral Imagery
Chapter 10 Machine Learning and Statistical Approaches for Plant
Phenotyping Chapter 11 A Brief Introduction to Machine Learning and Deep
Learning for Computer Vision PART III Practice Chapter 12 Chlorophyll a
Fluorescence Analyses to Investigate the Impacts of Genotype, Species, and
Stress on Photosynthetic Efficiency and Plant Productivity Chapter 13
Predicting Yield by Modeling Interactions between Canopy Coverage Image
Data, Genotypic and Environmental Information for Soybeans Chapter 14 Field
Phenotyping for Salt Tolerance and Imaging Techniques for Crop Stress
Biology Chapter 15 The Adoption of Automated Phenotyping by Plant Breeders