Machine Vision And Machine Learning For Plant Phenotyping And Precision Agriculture
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Machine Vision And Machine Learning For Plant Phenotyping And Precision Agriculture
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Author : Huajian Liu
language : en
Publisher: Frontiers Media SA
Release Date : 2024-01-18
Machine Vision And Machine Learning For Plant Phenotyping And Precision Agriculture written by Huajian Liu and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-01-18 with Science categories.
Plant phenotyping (PP) describes the physiological and biochemical properties of plants affected by both genotypes and environments. It is an emerging research field that is assisting the breeding and cultivation of new crop varieties to be more productive and resilient to challenging environments. Precision agriculture (PA) uses sensing technologies to observe crops and then manage them optimally to ensure that they grow in healthy conditions, have maximum productivity, and have minimal negative effects on the environment. Traditionally, the observation of plant traits heavily relies on human experts which is labor intensive, time-consuming, and subjective. Automatic crop traits measurement in PP and PA are two different fields, but they share the same sensing and data processing technologies in many respects. Recently, driven by computer and sensor technologies, machine vision (MV) and machine learning (ML) have contributed to accurate, high-throughput, and nondestructive plant phenotyping and precision agriculture. However, these technologies are still in their infant stage and there are many challenges and questions related to them that still need to be addressed. The goal of this Research Topic is to provide a platform to share the latest research results on the application of MV and ML for PP and PA. It aims to highlight cutting-edge technologies, bottle-necks, and future research directions for MV and ML in crop breeding, crop cultivation, disease management, weed control, and pest control.
Ai Sensors And Robotics In Plant Phenotyping And Precision Agriculture Volume Ii
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Author : Yongliang Qiao
language : en
Publisher: Frontiers Media SA
Release Date : 2023-07-03
Ai Sensors And Robotics In Plant Phenotyping And Precision Agriculture Volume Ii written by Yongliang Qiao and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-07-03 with Science categories.
Iot And Ai In Agriculture
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Author : Tofael Ahamed
language : en
Publisher: Springer Nature
Release Date :
Iot And Ai In Agriculture written by Tofael Ahamed and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.
Computer Vision And Machine Learning In Agriculture Volume 3
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Author : Jagdish Chand Bansal
language : en
Publisher: Springer Nature
Release Date : 2023-07-31
Computer Vision And Machine Learning In Agriculture Volume 3 written by Jagdish Chand Bansal and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-07-31 with Technology & Engineering categories.
This book is as an extension of the previous two volumes on “Computer Vision and Machine Learning in Agriculture”. This volume 3 discusses solutions to the problems of agricultural production by rendering advanced machine learning including deep learning tools and techniques. The book contains 13 chapters that focus on in-depth research outputs in precision agriculture, crop farming, horticulture, floriculture, vertical farming, animal husbandry, disease detection, plant recognition, production yield, product quality, defect assessment, and overall automation through robots and drones. The topics covered in the current volume, along with the previous volumes, are comprehensive literature for both beginners and experienced in this domain.
Computer Vision And Machine Learning In Agriculture Volume 2
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Author : Mohammad Shorif Uddin
language : en
Publisher: Springer Nature
Release Date : 2022-03-13
Computer Vision And Machine Learning In Agriculture Volume 2 written by Mohammad Shorif Uddin and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-03-13 with Technology & Engineering categories.
This book is as an extension of previous book “Computer Vision and Machine Learning in Agriculture” for academicians, researchers, and professionals interested in solving the problems of agricultural plants and products for boosting production by rendering the advanced machine learning including deep learning tools and techniques to computer vision algorithms. The book contains 15 chapters. The first three chapters are devoted to crops harvesting, weed, and multi-class crops detection with the help of robots and UAVs through machine learning and deep learning algorithms for smart agriculture. Next, two chapters describe agricultural data retrievals and data collections. Chapters 6, 7, 8 and 9 focuses on yield estimation, crop maturity detection, agri-food product quality assessment, and medicinal plant recognition, respectively. The remaining six chapters concentrates on optimized disease recognition through computer vision-based machine and deep learning strategies.
High Throughput Crop Phenotyping
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Author : Jianfeng Zhou
language : en
Publisher: Springer Nature
Release Date : 2021-07-17
High Throughput Crop Phenotyping written by Jianfeng Zhou and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-07-17 with Science categories.
This book provides an overview of the innovations in crop phenotyping using emerging technologies, i.e., high-throughput crop phenotyping technology, including its concept, importance, breakthrough and applications in different crops and environments. Emerging technologies in sensing, machine vision and high-performance computing are changing the world beyond our imagination. They are also becoming the most powerful driver of the innovation in agriculture technology, including crop breeding, genetics and management. It includes the state of the art of technologies in high-throughput phenotyping, including advanced sensors, automation systems, ground-based or aerial robotic systems. It also discusses the emerging technologies of big data processing and analytics, such as advanced machine learning and deep learning technologies based on high-performance computing infrastructure. The applications cover different organ levels (root, shoot and seed) of different crops (grains, soybean, maize, potato) at different growth environments (open field and controlled environments). With the contribution of more than 20 world-leading researchers in high-throughput crop phenotyping, the authors hope this book provides readers the needed information to understand the concept, gain the insides and create the innovation of high-throughput phenotyping technology.
Ai Sensors And Robotics In Plant Phenotyping And Precision Agriculture
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Author : Yongliang Qiao
language : en
Publisher: Frontiers Media SA
Release Date : 2022-12-27
Ai Sensors And Robotics In Plant Phenotyping And Precision Agriculture written by Yongliang Qiao and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-12-27 with Science categories.
Computer Vision And Machine Learning In Agriculture
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Author : Mohammad Shorif Uddin
language : en
Publisher:
Release Date : 2021
Computer Vision And Machine Learning In Agriculture written by Mohammad Shorif Uddin and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with categories.
This book discusses computer vision, a noncontact as well as a nondestructive technique involving the development of theoretical and algorithmic tools for automatic visual understanding and recognition which finds huge applications in agricultural productions. It also entails how rendering of machine learning techniques to computer vision algorithms is boosting this sector with better productivity by developing more precise systems. Computer vision and machine learning (CV-ML) helps in plant disease assessment along with crop condition monitoring to control the degradation of yield, quality, and severe financial loss for farmers. Significant scientific and technological advances have been made in defect assessment, quality grading, disease recognition, pests, insects, fruits, and vegetable types recognition and evaluation of a wide range of agricultural plants, crops, leaves, and fruits. The book discusses intelligent robots developed with the touch of CV-ML which can help farmers to perform various tasks like planting, weeding, harvesting, plant health monitoring, and so on. The topics covered in the book include plant, leaf, and fruit disease detection, crop health monitoring, applications of robots in agriculture, precision farming, assessment of product quality and defects, pest, insect, fruits, and vegetable types recognition.
Machine Learning And Deep Learning For Smart Agriculture And Applications
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Author : Hashmi, Mohamamd Farukh
language : en
Publisher: IGI Global
Release Date : 2023-08-29
Machine Learning And Deep Learning For Smart Agriculture And Applications written by Hashmi, Mohamamd Farukh and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-08-29 with Technology & Engineering categories.
Machine Learning and Deep Learning for Smart Agriculture and Applications delves into the captivating realm of artificial intelligence and its pivotal role in transforming the landscape of modern agriculture. With a focus on precision agriculture, digital farming, and emerging concepts, this book illuminates the significance of sustainable food production and resource management in the face of evolving digital hardware and software technologies. Geospatial technology, robotics, the Internet of Things (IoT), and data analytics converge with machine learning and big data to unlock new possibilities in agricultural management. This book explores the synergy between these disciplines, offering cutting-edge insights into data-intensive processes within operational agricultural environments. From automated irrigation systems and agricultural drones for field analysis to crop monitoring and precision agriculture, the applications of machine learning are far-reaching. Animal identification and health monitoring also benefit from these advanced techniques. With practical case studies on vegetable and fruit leaf disease detection, drone-based agriculture, and the impact of pesticides on plants, this book provides a comprehensive understanding of the applications of machine learning and deep learning in smart agriculture. It also examines various modeling techniques employed in this field and showcases how artificial intelligence can revolutionize plant disease detection. This book serves as a comprehensive guide for researchers, practitioners, and students seeking to harness the power of AI in transforming the agricultural landscape.
Precision Agriculture For Sustainability
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Author : Narendra Khatri
language : en
Publisher: CRC Press
Release Date : 2024-02-13
Precision Agriculture For Sustainability written by Narendra Khatri and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-02-13 with Technology & Engineering categories.
This new book delves into how modern technologies—i.e., global positioning systems (GPS), unmanned aerial vehicles (drones), image processing methods, artificial intelligence, machine learning, and deep learning—are being used to make agriculture more farmer-friendly and more economically profitable. The volume focuses on the use of smart sensors, actuators, and decision support systems to provide intelligent data about crop health and for monitoring for yield prediction, soil quality, nutrition requirement prediction, etc. The authors discuss robotic-based innovations in agriculture, soft computing methodologies for crop forecasting, machine learning techniques to classify and identify plant diseases, deep convolutional neural networks for recognizing nutrient deficiencies, and more.
