Computer Vision And Machine Learning In Agriculture
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Computer Vision and Machine Learning in Agriculture Volume 2
Author | : Mohammad Shorif Uddin,Jagdish Chand Bansal |
Publsiher | : Springer Nature |
Total Pages | : 269 |
Release | : 2022-03-13 |
Genre | : Technology & Engineering |
ISBN | : 9789811699917 |
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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.
Computer Vision and Machine Learning in Agriculture Volume 3
Author | : Jagdish Chand Bansal,Mohammad Shorif Uddin |
Publsiher | : Springer Nature |
Total Pages | : 215 |
Release | : 2023-07-31 |
Genre | : Technology & Engineering |
ISBN | : 9789819937547 |
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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
![Computer Vision and Machine Learning in Agriculture](https://youbookinc.com/wp-content/uploads/2024/06/cover.jpg)
Author | : Mohammad Shorif Uddin,Jagdish Chand Bansal |
Publsiher | : Unknown |
Total Pages | : 0 |
Release | : 2021 |
Genre | : Electronic Book |
ISBN | : 9813364254 |
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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.
Artificial Intelligence in Agriculture
Author | : Rajesh Singh,Anita Gehlot,Mahesh Kumar Prajapat,Bhupendra Singh |
Publsiher | : CRC Press |
Total Pages | : 186 |
Release | : 2021-11-23 |
Genre | : Technology & Engineering |
ISBN | : 9781000506211 |
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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.
Application of Machine Learning in Agriculture
Author | : Mohammad Ayoub Khan,Rijwan Khan,Mohammad Aslam Ansari |
Publsiher | : Academic Press |
Total Pages | : 332 |
Release | : 2022-05-14 |
Genre | : Business & Economics |
ISBN | : 9780323906685 |
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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
Artificial Intelligence for Biology and Agriculture
Author | : S. Panigrahi,K.C. Ting |
Publsiher | : Springer Science & Business Media |
Total Pages | : 258 |
Release | : 2012-12-06 |
Genre | : Technology & Engineering |
ISBN | : 9789401150484 |
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This volume contains a total of thirteen papers covering a variety of AI topics ranging from computer vision and robotics to intelligent modeling, neural networks and fuzzy logic. There are two general articles on robotics and fuzzy logic. The article on robotics focuses on the application of robotics technology in plant production. The second article on fuzzy logic provides a general overview of the basics of fuzzy logic and a typical agricultural application of fuzzy logic. The article `End effectors for tomato harvesting' enhances further the robotic research as applied to tomato harvesting. The application of computer vision techniques for different biological/agricultural applications, for example, length determination of cheese threads, recognition of plankton images and morphological identification of cotton fibers, depicts the complexity and heterogeneities of the problems and their solutions. The development of a real-time orange grading system in the article `Video grading of oranges in real-time' further reports the capability of computer vision technology to meet the demand of high quality food products. The integration of neural network technology with computer vision and fuzzy logic for defect detection in eggs and identification of lettuce growth shows the power of hybridization of AI technologies to solve agricultural problems. Additional papers also focus on automated modeling of physiological processes during postharvest distribution of agricultural products, the applications of neural networks, fusion of AI technologies and three dimensional computer vision technologies for different problems ranging from botanical identification and cell migration analysis to food microstructure evaluation.
Internet of Things and Machine Learning in Agriculture
Author | : Jyotir Moy Chatterjee,Abhishek Kumar,Pramod Singh Rathore,Vishal Jain |
Publsiher | : Walter de Gruyter GmbH & Co KG |
Total Pages | : 454 |
Release | : 2021-02-08 |
Genre | : Computers |
ISBN | : 9783110691283 |
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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.
Applications of Computer Vision and Drone Technology in Agriculture 4 0
Author | : Siddharth Singh Chouhan |
Publsiher | : Springer Nature |
Total Pages | : 332 |
Release | : 2024 |
Genre | : Electronic Book |
ISBN | : 9789819986842 |
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