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Convolutional Neural Networks And Deep Learning For Crop Improvement And Production
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Book Synopsis Convolutional neural networks and deep learning for crop improvement and production by : Wanneng Yang
Download or read book Convolutional neural networks and deep learning for crop improvement and production written by Wanneng Yang and published by Frontiers Media SA. This book was released on 2023-01-04 with total page 208 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Recent Advances in Big Data, Machine, and Deep Learning for Precision Agriculture by : Muhammad Fazal Ijaz
Download or read book Recent Advances in Big Data, Machine, and Deep Learning for Precision Agriculture written by Muhammad Fazal Ijaz and published by Frontiers Media SA. This book was released on 2024-02-19 with total page 379 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Computer Vision and Machine Learning in Agriculture, Volume 2 by : Mohammad Shorif Uddin
Download or read book Computer Vision and Machine Learning in Agriculture, Volume 2 written by Mohammad Shorif Uddin and published by Springer Nature. This book was released on 2022-03-13 with total page 269 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Application of Machine Learning in Agriculture by : Mohammad Ayoub Khan
Download or read book Application of Machine Learning in Agriculture written by Mohammad Ayoub Khan and published by Academic Press. This book was released on 2022-05-14 with total page 332 pages. Available in PDF, EPUB and Kindle. Book excerpt: Application of Machine Learning in Smart Agriculture is the first book to present a multidisciplinary look at how technology can not only improve agricultural output, but the economic efficiency of that output as well. Through a global lens, the book approaches the subject from a technical perspective, providing important knowledge and insights for effective and efficient implementation and utilization of machine learning. As artificial intelligence techniques are being used to increase yield through optimal planting, fertilizing, irrigation, and harvesting, these are only part of the complex picture which must also take into account the economic investment and its optimized return. The performance of machine learning models improves over time as the various mathematical and statistical models are proven. Presented in three parts, Application of Machine Learning in Smart Agriculture looks at the fundamentals of smart agriculture; the economics of the technology in the agricultural marketplace; and a diverse representation of the tools and techniques currently available, and in development. This book is an important resource for advanced level students and professionals working with artificial intelligence, internet of things, technology and agricultural economics. Addresses the technology of smart agriculture from a technical perspective Reveals opportunities for technology to improve and enhance not only yield and quality, but the economic value of a food crop Discusses physical instruments, simulations, sensors, and markets for machine learning in agriculture
Book Synopsis Machine Learning and Deep Learning for Smart Agriculture and Applications by : Hashmi, Mohamamd Farukh
Download or read book Machine Learning and Deep Learning for Smart Agriculture and Applications written by Hashmi, Mohamamd Farukh and published by IGI Global. This book was released on 2023-08-29 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Machine Vision and Machine Learning for Plant Phenotyping and Precision Agriculture by : Huajian Liu
Download or read book Machine Vision and Machine Learning for Plant Phenotyping and Precision Agriculture written by Huajian Liu and published by Frontiers Media SA. This book was released on 2024-01-18 with total page 423 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Deep Learning for Sustainable Agriculture by : Ramesh Chandra Poonia
Download or read book Deep Learning for Sustainable Agriculture written by Ramesh Chandra Poonia and published by Academic Press. This book was released on 2022-01-09 with total page 408 pages. Available in PDF, EPUB and Kindle. Book excerpt: The evolution of deep learning models, combined with with advances in the Internet of Things and sensor technology, has gained more importance for weather forecasting, plant disease detection, underground water detection, soil quality, crop condition monitoring, and many other issues in the field of agriculture. agriculture. Deep Learning for Sustainable Agriculture discusses topics such as the impactful role of deep learning during the analysis of sustainable agriculture data and how deep learning can help farmers make better decisions. It also considers the latest deep learning techniques for effective agriculture data management, as well as the standards established by international organizations in related fields. The book provides advanced students and professionals in agricultural science and engineering, geography, and geospatial technology science with an in-depth explanation of the relationship between agricultural inference and the decision-support amenities offered by an advanced mathematical evolutionary algorithm. Introduces new deep learning models developed to address sustainable solutions for issues related to agriculture Provides reviews on the latest intelligent technologies and algorithms related to the state-of-the-art methodologies of monitoring and mitigation of sustainable agriculture Illustrates through case studies how deep learning has been used to address a variety of agricultural diseases that are currently on the cutting edge Delivers an accessible explanation of artificial intelligence algorithms, making it easier for the reader to implement or use them in their own agricultural domain
Book Synopsis Artificial Intelligence Applications in Specialty Crops by : Yiannis Ampatzidis
Download or read book Artificial Intelligence Applications in Specialty Crops written by Yiannis Ampatzidis and published by Frontiers Media SA. This book was released on 2022-03-02 with total page 444 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Translating Physiological Tools to Augment Crop Breeding by : Mamrutha Harohalli Masthigowda
Download or read book Translating Physiological Tools to Augment Crop Breeding written by Mamrutha Harohalli Masthigowda and published by Springer Nature. This book was released on 2023-04-19 with total page 460 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers different physiological processes, tools, and their application in crop breeding. Each chapter emphasizes on a specific trait/physiological process and its importance in crop, their phenotyping information and how best it can be employed for crop improvement by projecting on success stories in different crops. It covers wide range of physiological topics including advances in field phenotyping, role of endophytic fungi, metabolomics, application of stable isotopes, high throughput phenomics, transpiration efficiency, root phenotyping and root exudates for improved resource use efficiency, cuticular wax and its application, advances in photosynthetic studies, leaf spectral reflectance and physiological breeding in hardy crops like millets. This book also covers the futuristic research areas like artificial intelligence and machine learning. This contributed volume compiles all application parts of physiological tools along with their advanced research in these areas, which is very much need of the hour for both academics and researchers for ready reference. This book will be of interest to teachers, researchers, climate change scientists, capacity builders, and policy makers. Also, the book serves as additional reading material for undergraduate and graduate students of agriculture, physiology, botany, ecology, and environmental sciences. National and international agricultural scientists will also find this a useful resource.
Book Synopsis Deep Learning for Agricultural Visual Perception by : Rujing Wang
Download or read book Deep Learning for Agricultural Visual Perception written by Rujing Wang and published by Springer Nature. This book was released on 2023-09-20 with total page 140 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph provides a detailed and systematic introduction to the application of deep learning technology in the intelligent monitoring of crop diseases and pests. Taking 24 types of crop pests, wheat aphids, and wheat diseases with complex backgrounds as examples, a large-scale crop pest and disease dataset was constructed to provide necessary data support for the deep learning module. Various schemes for identifying and detecting large-scale crop diseases and pests based on deep convolutional neural network technology have also been proposed. This book can be used as a reference for teachers and students majoring in agriculture, computer science, artificial intelligence, intelligent science and technology, and other related fields in higher education institutions. It can also be used as a reference book for researchers in fields such as image processing technology, intelligent manufacturing, and high-tech applications.
Book Synopsis Internet of Things and Machine Learning in Agriculture by : Jyotir Moy Chatterjee
Download or read book Internet of Things and Machine Learning in Agriculture written by Jyotir Moy Chatterjee and published by Walter de Gruyter GmbH & Co KG. This book was released on 2021-02-08 with total page 454 pages. Available in PDF, EPUB and Kindle. Book excerpt: Agriculture is one of the most fundamental human activities. As the farming capacity has expanded, the usage of resources such as land, fertilizer, and water has grown exponentially, and environmental pressures from modern farming techniques have stressed natural landscapes. Still, by some estimates, worldwide food production needs to increase to keep up with global food demand. Machine Learning and the Internet of Things can play a promising role in the Agricultural industry, and help to increase food production while respecting the environment. This book explains how these technologies can be applied, offering many case studies developed in the research world.
Book Synopsis Advanced Technologies for Smart Agriculture by : Kalaiselvi K.
Download or read book Advanced Technologies for Smart Agriculture written by Kalaiselvi K. and published by CRC Press. This book was released on 2024-02-27 with total page 425 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book brings new smart farming methodologies to the forefront, sparked by pervasive applications with automated farming technology. New indigenous expertise on smart agricultural technologies is presented along with conceptual prototypes showing how the Internet of Things, cloud computing, machine learning, deep learning, precision farming, crop management systems, etc., will be used in large-scale production in the future. The necessity of available welfare systems for farmers’ well-being is also discussed in the book. It draws the conclusion that there is a greater need and demand today for smart farming methodologies driven by technology than ever before.
Book Synopsis IoT, UAV, BCI Empowered Deep Learning models in Precision Agriculture by : José Dias Pereira
Download or read book IoT, UAV, BCI Empowered Deep Learning models in Precision Agriculture written by José Dias Pereira and published by Frontiers Media SA. This book was released on 2024-05-10 with total page 245 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine vision applications in precision agriculture have attracted a great deal of attention. They focus on monitoring, protection, and management of various plant populations. These applications have shown potential value in reforming crucial components of plant production, including fine-grained ripeness recognition of all kinds of plants and detecting and classifying weeds, seeds, and pests for crop health, quality, and quantity enhancement. In recent decades, the extensive achievements of deep learning techniques have shown significant opportunities for almost all fields. Accordingly, many deep learning models have been presented for different types of images and have achieved promising outcomes. The deep learning-based approaches can contribute to gaining insights into the plants' inherent characteristics and the surrounding environmental elements. This research topic's primary value is providing a platform for deep learning-based applications for precision agriculture. These applications can be fairly evaluated and compared with each other. Accordingly, more effective and efficient detection and classification approaches for precision agriculture can be developed or optimized.
Book Synopsis Artificial Neural Networks in Agriculture by : Sebastian Kujawa
Download or read book Artificial Neural Networks in Agriculture written by Sebastian Kujawa and published by Mdpi AG. This book was released on 2021-11-11 with total page 284 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modern agriculture needs to have high production efficiency combined with a high quality of obtained products. This applies to both crop and livestock production. To meet these requirements, advanced methods of data analysis are more and more frequently used, including those derived from artificial intelligence methods. Artificial neural networks (ANNs) are one of the most popular tools of this kind. They are widely used in solving various classification and prediction tasks, for some time also in the broadly defined field of agriculture. They can form part of precision farming and decision support systems. Artificial neural networks can replace the classical methods of modelling many issues, and are one of the main alternatives to classical mathematical models. The spectrum of applications of artificial neural networks is very wide. For a long time now, researchers from all over the world have been using these tools to support agricultural production, making it more efficient and providing the highest-quality products possible.
Book Synopsis Computer Vision and Machine Learning in Agriculture, Volume 3 by : Jagdish Chand Bansal
Download or read book Computer Vision and Machine Learning in Agriculture, Volume 3 written by Jagdish Chand Bansal and published by Springer Nature. This book was released on 2023-07-31 with total page 215 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Advances in Agronomy written by and published by Elsevier. This book was released on 2024-02-01 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advances in Agronomy, Volume 184, the latest release in this leading reference on agronomy, contains a variety of updates and highlights new advances in the field. Each chapter is written by an international board of authors, with this new release including new chapters on The Role of Artificial Intelligence in Crop Improvement, Dealing with the Impact of Climate Change-Induced Drought on the Management of Soil, Challenges and Emerging Opportunities of Weed Management in Organic Agriculture, The Broadbalk Wheat Experiment, Rothamsted, UK: Crop Yields and Soil Changes During the Last 50 Years. Includes numerous, timely, state-of-the-art reviews on the latest advancements in agronomy Features distinguished, well recognized authors from around the world Builds upon this venerable and iconic review series Covers the extensive variety and breadth of subject matter in the crop and soil sciences
Book Synopsis Artificial Intelligence Applications in Agriculture and Food Quality Improvement by : Khan, Mohammad Ayoub
Download or read book Artificial Intelligence Applications in Agriculture and Food Quality Improvement written by Khan, Mohammad Ayoub and published by IGI Global. This book was released on 2022-05-27 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: Food is a necessary aspect of human life, and agriculture is crucial to any country’s global economy. Because the food business is essential to both a country’s economy and global economy, artificial intelligence (AI)-based smart solutions are needed to assure product quality and food safety. The agricultural sector is constantly under pressure to boost crop output as a result of population growth. This necessitates the use of AI applications. Artificial Intelligence Applications in Agriculture and Food Quality Improvement discusses the application of AI, machine learning, and data analytics for the acceleration of the agricultural and food sectors. It presents a comprehensive view of how these technologies and tools are used for agricultural process improvement, food safety, and food quality improvement. Covering topics such as diet assessment research, crop yield prediction, and precision farming, this premier reference source is an essential resource for food safety professionals, quality assurance professionals, agriculture specialists, crop managers, agricultural engineers, food scientists, computer scientists, AI specialists, students, libraries, government officials, researchers, and academicians.
