Download or read book Computer Vision and Machine Learning Applications for Dairy Farming written by Rafael Ehrich Pontes Ferreira and published by . This book was released on 2024 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: With recent advancements in precision livestock farming (PLF) and machine learning (ML) techniques, computer vision systems (CVS) have gained popularity as powerful tools for individual animal monitoring. These systems can capture phenotypes from multiple animals simultaneously in an automated and non-intrusive manner. Individual animal identification is crucial for matching animals with their predicted phenotypes, which can be achieved through external identification systems or computer vision-based animal identification algorithms. While previous studies have focused on using computer vision techniques for identifying dairy cows based on unique coat color patterns, these methods are limited to specific breeds that present such patterns. Furthermore, there is a lack of research on the long-term applicability of these methods, considering visual changes due to growth or physiological states. Chapter 1 discusses current applications of computer vision for animal identification, while Chapter 2 explores methods using 3-dimensional representations of the dorsal surface of dairy calves for identification without relying on coat color patterns. These methods are evaluated on calves during their growth stage, accounting for changes in body shape and size. In Chapter 3, the potential of pseudo-labeling is assessed for improving the performance of neural networks for animal identification. The results show promising performance with a fraction of annotated data compared to traditional methods. Chapters 4 and 5 focus on developing machine learning pipelines for phenotype prediction, specifically early detection of postpartum subclinical ketosis (SCK) using prepartum data exclusively. Various techniques are explored for extracting features from image, text, genotype, and cow behavior and historical data. Data fusion techniques are explored to integrate those features into the machine learning pipelines, and a cloud computing-based framework is proposed to automate data processing, feature extraction, and phenotype prediction. Overall, this dissertation highlights the potential of machine learning and computer vision in guiding data-driven management decisions in dairy farming. By automating processes and integrating data from multiple sources and modalities, these techniques offer opportunities for improving farm profitability, productivity, and animal welfare, particularly through individual animal monitoring and early detection of health issues.

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.

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 Data Driven Farming written by Syed Nisar Hussain Bukhari and published by CRC Press. This book was released on 2024-06-13 with total page 301 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the dynamic realm of agriculture, artificial intelligence (AI) and machine learning (ML) emerge as catalysts for unprecedented transformation and growth. The emergence of big data, Internet of Things (IoT) sensors, and advanced analytics has opened up new possibilities for farmers to collect and analyze data in real-time, make informed decisions, and increase efficiency. AI and ML are key enablers of data-driven farming, allowing farmers to use algorithms and predictive models to gain insights into crop health, soil quality, weather patterns, and more. Agriculture is an industry that is deeply rooted in tradition, but the landscape is rapidly changing with the emergence of new technologies. Data-Driven Farming: Harnessing the Power of AI and Machine Learning in Agriculture is a comprehensive guide that explores how the latest advances in technology can help farmers make better decisions and maximize yields. It offers a detailed overview of the intersection of data, AI, and ML in agriculture and offers real-world examples and case studies that demonstrate how these tools can help farmers improve efficiency, reduce waste, and increase profitability. Exploring how AI and ML can be used to achieve sustainable and profitable farming practices, the book provides an introduction to the basics of data-driven farming, including an overview of the key concepts, tools, and technologies. It also discusses the challenges and opportunities facing farmers in today’s data-driven landscape. Covering such topics as crop monitoring, weather forecasting, pest management, and soil health management, the book focuses on analyzing data, predicting outcomes, and optimizing decision-making in a range of agricultural contexts.

Download or read book Computer Vision and Machine Learning in Agriculture written by Mohammad Shorif Uddin and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

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.

Download or read book Artificial Intelligence in Agriculture written by Rajesh Singh and published by CRC Press. This book was released on 2021-11-23 with total page 186 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a platform for anyone who wishes to explore Artificial Intelligence in the field of agriculture from scratch or broaden their understanding and its uses. This book offers a practical, hands-on exploration of Artificial Intelligence, machine learning, deep Learning, computer vision and Expert system with proper examples to understand. This book also covers the basics of python with example so that any anyone can easily understand and utilize artificial intelligence in agriculture field. This book is divided into two parts wherein first part talks about the artificial intelligence and its impact in the agriculture with all its branches and their basics. The second part of the book is purely implementation of algorithms and use of different libraries of machine learning, deep learning and computer vision to build useful and sightful projects in real time which can be very useful for you to have better understanding of artificial intelligence. After reading this book, the reader will an understanding of what Artificial Intelligence is, where it is applicable, and what are its different branches, which can be useful in different scenarios. The reader will be familiar with the standard workflow for approaching and solving machine-learning problems, and how to address commonly encountered issues. The reader will be able to use Artificial Intelligence to tackle real-world problems ranging from crop health prediction to field surveillance analytics, classification to recognition of species of plants etc. Note: T&F does not sell or distribute the hardback in India, Pakistan, Nepal, Bhutan, Bangladesh and Sri Lanka. This title is co-published with NIPA.

Download or read book Applications of Computer Vision and Drone Technology in Agriculture 4 0 written by Siddharth Singh Chouhan and published by Springer Nature. This book was released on with total page 332 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Nutrient Requirements of Dairy Cattle written by National Research Council and published by National Academies Press. This book was released on 2001-02-09 with total page 406 pages. Available in PDF, EPUB and Kindle. Book excerpt: This widely used reference has been updated and revamped to reflect the changing face of the dairy industry. New features allow users to pinpoint nutrient requirements more accurately for individual animals. The committee also provides guidance on how nutrient analysis of feed ingredients, insights into nutrient utilization by the animal, and formulation of diets to reduce environmental impacts can be applied to productive management decisions. The book includes a user-friendly computer program on a compact disk, accompanied by extensive context-sensitive "Help" options, to simulate the dynamic state of animals. The committee addresses important issues unique to dairy science-the dry or transition cow, udder edema, milk fever, low-fat milk, calf dehydration, and more. The also volume covers dry matter intake, including how to predict feed intake. It addresses the management of lactating dairy cows, utilization of fat in calf and lactation diets, and calf and heifer replacement nutrition. In addition, the many useful tables include updated nutrient composition for commonly used feedstuffs.

Download or read book Applications of Optimization and Machine Learning in Image Processing and IoT written by Nidhi Gupta and published by CRC Press. This book was released on 2023-12-01 with total page 236 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents state-of-the-art optimization algorithms followed by Internet of Things (IoT) fundamentals. The applications of machine learning and IoT are explored, with topics including optimization, algorithms and machine learning in image processing and IoT. Applications of Optimization and Machine Learning in Image Processing and IoT is a complete reference source, providing the latest research findings and solutions for optimization and machine learning algorithms. The chapters examine and discuss the fields of machine learning, IoT and image processing. KEY FEATURES: • Includes fundamental concepts towards advanced applications in machine learning and IoT. • Discusses potential and challenges of machine learning for IoT and optimization • Reviews recent advancements in diverse researches on computer vision, networking and optimization field. • Presents latest technologies such as machine learning in image processing and IoT This book has been written for readers in academia, engineering, IT specialists, researchers, industrial professionals and students, and is a great reference for those just starting out in the field as well as those at an advanced level.

Download or read book Machine Learning and Computational Intelligence Techniques for Data Engineering written by Pradeep Singh and published by Springer Nature. This book was released on 2023-05-15 with total page 885 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book comprises the proceedings of the 4th International Conference on Machine Intelligence and Signal Processing (MISP2022). The contents of this book focus on research advancements in machine intelligence, signal processing, and applications. The book covers the real-time challenges involved while processing big data analytics and stream processing with the integration of smart data computing services and interconnectivity. It also includes the progress in signal processing to process the normal and abnormal categories of real-world signals such as signals generated from IoT devices, smart systems, speech, videos and involves biomedical signal processing: electrocardiogram (ECG), electroencephalogram (EEG), magnetoencephalography (MEG), electromyogram (EMG), etc. This book proves to be a valuable resource for those in academia and industry.

Download or read book NorFor written by Harald Volden and published by Springer Science & Business Media. This book was released on 2011-10-05 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt: NorFor is a semi-mechanistic feed evaluation system for cattle, which is used by advisors in Denmark, Iceland, Norway and Sweden. This book describes in detail the system and it covers five main sections. The first is concerned with information on feed characteristics, feed analysis and feed digestion methods. The second section describes the digestion and metabolism in the gastrointestinal tract and the supply and requirement of energy and metabolizable amino acids. The third section considers the prediction of feed intake and physical structure of the diet. The fourth section focuses on model evaluation and the final section provides information on the IT solutions and feed ration formulation by a non-linear economical optimization procedure. This book will be of significant interest to researchers, students and advisors of cattle nutrition and feed evaluation.

Download or read book Applications of Image Processing and Soft Computing Systems in Agriculture written by Razmjooy, Navid and published by IGI Global. This book was released on 2019-02-22 with total page 337 pages. Available in PDF, EPUB and Kindle. Book excerpt: The variety and abundance of qualitative characteristics of agricultural products have been the main reasons for the development of different types of non-destructive methods (NDTs). Quality control of these products is one of the most important tasks in manufacturing processes. The use of control and automation has become more widespread, and new approaches provide opportunities for production competition through new technologies. Applications of Image Processing and Soft Computing Systems in Agriculture examines applications of artificial intelligence in agriculture and the main uses of shape analysis on agricultural products such as relationships between form and genetics, adaptation, product characteristics, and product sorting. Additionally, it provides insights developed through computer vision techniques. Highlighting such topics as deep learning, agribusiness, and augmented reality, it is designed for academicians, researchers, agricultural practitioners, and industry professionals.

Download or read book Leveraging Computer Vision to Biometric Applications written by Arvind Selwal and published by CRC Press. This book was released on 2024-10-07 with total page 358 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computer vision is an effective solution in a diverse range of real-life applications. With the advent of the machine and deep learning paradigms, this book adopts machine and deep learning algorithms to leverage digital image processing for designing accurate biometrical applications. In this aspect, it presents the advancements made in computer vision to biometric applications design approach using emerging technologies. It discusses the challenges of designing efficient and accurate biometric-based systems, which is a key issue that can be tackled via computer vision-based techniques. Key Features • Discusses real-life applications of emerging techniques in computer vision systems • Offers solutions on real-time computer vision and biometrics applications to cater to the needs of current industry • Presents case studies to offer ideas for developing new biometrics-based products • Offers problem-based solutions in the field computer vision and real-time biometric applications for secured human authentication • Works as a ready resource for professionals and scholars working on emerging topics of computer vision for biometrics. The book is for academic researchers, scholars and students in Computer Science, Information Technology, Electronics and Electrical Engineering, Mechanical Engineering, management, academicians, researchers, scientists and industry people working on computer vision and biometrics applications.

Download or read book Machine Learning and Big Data Analytics written by Rajiv Misra and published by Springer Nature. This book was released on 2023-06-06 with total page 552 pages. Available in PDF, EPUB and Kindle. Book excerpt: This edited volume on machine learning and big data analytics (Proceedings of ICMLBDA 2022) is intended to be used as a reference book for researchers and professionals to share their research and reports of new technologies and applications in Machine Learning and Big Data Analytics like biometric Recognition Systems, medical diagnosis, industries, telecommunications, AI Petri Nets Model-Based Diagnosis, gaming, stock trading, Intelligent Aerospace Systems, robot control, law, remote sensing and scientific discovery agents and multiagent systems; and natural language and Web intelligence. The intent of this book is to provide awareness of algorithms used for machine learning and big data in the advanced Scientific Technologies, provide a correlation of multidisciplinary areas and become a point of great interest for Data Scientists, systems architects, developers, new researchers and graduate level students. This volume provides cutting-edge research from around the globe on this field. Current status, trends, future directions, opportunities, etc. are discussed, making it friendly for beginners and young researchers.

Download or read book Machine Vision for Industry 4 0 written by Roshani Raut and published by CRC Press. This book was released on 2022-03-23 with total page 322 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses the use of machine vision and technologies in specific engineering case studies and focuses on how machine vision techniques are impacting every step of industrial processes and how smart sensors and cognitive big data analytics are supporting the automation processes in Industry 4.0 applications. Industry 4.0, the Fourth Industrial Revolution, combines traditional manufacturing with automation and data exchange. Machine vision is used in the industry for reliable product inspections, quality control, and data capture solutions. It combines different technologies to provide important information from the acquisition and analysis of images for robot-based inspection and guidance. Features Presents a comprehensive guide on how to use machine vision for Industry 4.0 applications, such as analysis of images for automated inspections, object detection, object tracking, and more Includes case studies of Robotics Internet of Things with its current and future applications in healthcare, agriculture, and transportation Highlights the inclusion of impaired people in the industry, for example, an intelligent assistant that helps deaf-mute individuals to transmit instructions and warnings in a manufacturing process Examines the significant technological advancements in machine vision for Industrial Internet of Things and explores the commercial benefits using real-world applications from healthcare to transportation Discusses a conceptual framework of machine vision for various industrial applications The book addresses scientific aspects for a wider audience such as senior and junior engineers, undergraduate and postgraduate students, researchers, and anyone interested in the trends, development, and opportunities for machine vision for Industry 4.0 applications.

Download or read book Applications of Computer Vision and Drone Technology in Agriculture 4 0 written by Siddharth Singh Chouhan and published by Springer. This book was released on 2024-02-18 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This edited book focus on two most emerging areas and covers the different aspects of computer vision and drone technology in the field of agriculture. It comprises various applications including segmentation/classification of plant diseases, monitoring of crops, grade/quality estimation of fruits/flowers/vegetables/crops, surveillance, soil deficiency estimation, crop/plant growth estimation, canopy measurement, water stress management, vegetation indices calculation, weed detection, and spraying, among other. It has 17 chapters contributed by experts in the field of computer vision, drone technology, deep learning, machine learning, artificial intelligence, image processing, agriculturist, and plant pathologists. The recent development of high-end computing devices and the adaptation of unmanned aerial vehicles has provided a mechanism to automate traditional agriculture practices. The on-field or aerial images captured using cameras are processed with the help of intelligent algorithms, and an assessment is drawn for further recommendations. This practice is efficient in provisioning an accurate, timely, and economical decision-making system to overcome the problems of agricultural field experts and farmers. This process is advantageous in increasing the quality and quantity of crop yields. This book serves as an excellent guide to students, researchers, scientists, and field experts in directing their work toward this domain and developing/designing models. Further, this book is useful for pathologists, biotechnologists, seed production specialists, breeders, market managers, and other stakeholders associated with underlying technology or market development from the public and private sectors.