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Author: Han Zhongzhi
Publisher: CRC Press
ISBN: 1000691950
Category : Science
Languages : en
Pages : 379
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Book Description
In recent years, computer vision is a fast-growing technique of agricultural engineering, especially in quality detection of agricultural products and food safety testing. It can provide objective, rapid, non-contact and non-destructive methods by extracting quantitative information from digital images. Significant scientific and technological advances have been made in quality inspection, classification and evaluation of a wide range of food and agricultural products. Computer Vision-Based Agriculture Engineering focuses on these advances. The book contains 25 chapters covering computer vision, image processing, hyperspectral imaging and other related technologies in peanut aflatoxin, peanut and corn quality varieties, and carrot and potato quality, as well as pest and disease detection. Features: Discusses various detection methods in a variety of agricultural crops Each chapter includes materials and methods used, results and analysis, and discussion with conclusions Covers basic theory, technical methods and engineering cases Provides comprehensive coverage on methods of variety identification, quality detection and detection of key indicators of agricultural products safety Presents information on technology of artificial intelligence including deep learning and transfer learning Computer Vision-Based Agriculture Engineering is a summary of the author's work over the past 10 years. Professor Han has presented his most recent research results in all 25 chapters of this book. This unique work provides students, engineers and technologists working in research, development, and operations in agricultural engineering with critical, comprehensive and readily accessible information. It applies development of artificial intelligence theory and methods including depth learning and transfer learning to the field of agricultural engineering testing.
Author: Han Zhongzhi
Publisher: CRC Press
ISBN: 1000691950
Category : Science
Languages : en
Pages : 379
Get Book Here
Book Description
In recent years, computer vision is a fast-growing technique of agricultural engineering, especially in quality detection of agricultural products and food safety testing. It can provide objective, rapid, non-contact and non-destructive methods by extracting quantitative information from digital images. Significant scientific and technological advances have been made in quality inspection, classification and evaluation of a wide range of food and agricultural products. Computer Vision-Based Agriculture Engineering focuses on these advances. The book contains 25 chapters covering computer vision, image processing, hyperspectral imaging and other related technologies in peanut aflatoxin, peanut and corn quality varieties, and carrot and potato quality, as well as pest and disease detection. Features: Discusses various detection methods in a variety of agricultural crops Each chapter includes materials and methods used, results and analysis, and discussion with conclusions Covers basic theory, technical methods and engineering cases Provides comprehensive coverage on methods of variety identification, quality detection and detection of key indicators of agricultural products safety Presents information on technology of artificial intelligence including deep learning and transfer learning Computer Vision-Based Agriculture Engineering is a summary of the author's work over the past 10 years. Professor Han has presented his most recent research results in all 25 chapters of this book. This unique work provides students, engineers and technologists working in research, development, and operations in agricultural engineering with critical, comprehensive and readily accessible information. It applies development of artificial intelligence theory and methods including depth learning and transfer learning to the field of agricultural engineering testing.
Author: Han Zhongzhi
Publisher: CRC Press
ISBN: 1000691616
Category : Technology & Engineering
Languages : en
Pages : 349
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Book Description
In recent years, computer vision is a fast-growing technique of agricultural engineering, especially in quality detection of agricultural products and food safety testing. It can provide objective, rapid, non-contact and non-destructive methods by extracting quantitative information from digital images. Significant scientific and technological advances have been made in quality inspection, classification and evaluation of a wide range of food and agricultural products. Computer Vision-Based Agriculture Engineering focuses on these advances. The book contains 25 chapters covering computer vision, image processing, hyperspectral imaging and other related technologies in peanut aflatoxin, peanut and corn quality varieties, and carrot and potato quality, as well as pest and disease detection. Features: Discusses various detection methods in a variety of agricultural crops Each chapter includes materials and methods used, results and analysis, and discussion with conclusions Covers basic theory, technical methods and engineering cases Provides comprehensive coverage on methods of variety identification, quality detection and detection of key indicators of agricultural products safety Presents information on technology of artificial intelligence including deep learning and transfer learning Computer Vision-Based Agriculture Engineering is a summary of the author's work over the past 10 years. Professor Han has presented his most recent research results in all 25 chapters of this book. This unique work provides students, engineers and technologists working in research, development, and operations in agricultural engineering with critical, comprehensive and readily accessible information. It applies development of artificial intelligence theory and methods including depth learning and transfer learning to the field of agricultural engineering testing.
Author: Mohammad Shorif Uddin
Publisher: Springer Nature
ISBN: 9813364246
Category : Technology & Engineering
Languages : en
Pages : 172
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Book Description
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.
Author: Rajesh Singh
Publisher: CRC Press
ISBN: 1000506215
Category : Technology & Engineering
Languages : en
Pages : 186
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Book Description
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.
Author: Razmjooy, Navid
Publisher: IGI Global
ISBN: 152258028X
Category : Technology & Engineering
Languages : en
Pages : 358
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Book Description
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.
Author: Daoliang Li
Publisher: Springer
ISBN: 3642361374
Category : Computers
Languages : en
Pages : 504
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Book Description
The two-volume set IFIP AICT 392 and 393 constitutes the refereed post-conference proceedings of the 6th IFIP TC 5, SIG 5.1 International Conference on Computer and Computing Technologies in Agriculture, CCTA 2012, held in Zhangjiajie, China, in October 2012. The 108 revised papers presented were carefully selected from numerous submissions. They cover a wide range of interesting theories and applications of information technology in agriculture, including Internet of things and cloud computing; simulation models and decision-support systems for agricultural production; smart sensor, monitoring, and control technology; traceability and e-commerce technology; computer vision, computer graphics, and virtual reality; the application of information and communication technology in agriculture; and universal information service technology and service systems development in rural areas. The 55 papers included in the second volume focus on GIS, GPS, RS, and Precision Farming.
Author: Pradeep, N.
Publisher: IGI Global
ISBN: 1522596348
Category : Technology & Engineering
Languages : en
Pages : 310
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Book Description
Since agriculture is one of the key parameters in assessing the gross domestic product (GDP) of any country, it has become crucial to transition from traditional agricultural practices to smart agriculture. New agricultural technologies provide numerous opportunities to maximize crop yield by recognizing and analyzing diseases and other natural variables that may affect it. Therefore, it is necessary to understand how computer-assisted technologies can best be utilized and adopted in the conversion to smart agriculture. Modern Techniques for Agricultural Disease Management and Crop Yield Prediction is an essential publication that widens the spectrum of computational methods that can aid in agriculture disease management, weed detection, and crop yield prediction. Featuring coverage on a wide range of topics such as soil and crop sensors, swarm robotics, and weed detection, this book is ideally designed for environmentalists, farmers, botanists, agricultural engineers, computer engineers, scientists, researchers, practitioners, and students seeking current research on technology and techniques for agricultural diseases and predictive trends.
Author: Tomar, Pradeep
Publisher: IGI Global
ISBN: 1799817245
Category : Technology & Engineering
Languages : en
Pages : 400
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Book Description
As technology continues to saturate modern society, agriculture has started to adopt digital computing and data-driven innovations. This emergence of “smart” farming has led to various advancements in the field, including autonomous equipment and the collection of climate, livestock, and plant data. As connectivity and data management continue to revolutionize the farming industry, empirical research is a necessity for understanding these technological developments. Artificial Intelligence and IoT-Based Technologies for Sustainable Farming and Smart Agriculture provides emerging research exploring the theoretical and practical aspects of critical technological solutions within the farming industry. Featuring coverage on a broad range of topics such as crop monitoring, precision livestock farming, and agronomic data processing, this book is ideally designed for farmers, agriculturalists, product managers, farm holders, manufacturers, equipment suppliers, industrialists, governmental professionals, researchers, academicians, and students seeking current research on technological applications within agriculture and farming.
Author: Ajith Abraham
Publisher: Academic Press
ISBN: 0128236957
Category : Technology & Engineering
Languages : en
Pages : 578
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Book Description
AI, Edge, and IoT Smart Agriculture integrates applications of IoT, edge computing, and data analytics for sustainable agricultural development and introduces Edge of Thing-based data analytics and IoT for predictability of crop, soil, and plant disease occurrence for improved sustainability and increased profitability. The book also addresses precision irrigation, precision horticulture, greenhouse IoT, livestock monitoring, IoT ecosystem for agriculture, mobile robot for precision agriculture, energy monitoring, storage management, and smart farming. The book provides an overarching focus on sustainable environment and sustainable economic development through smart and e-agriculture. Providing a medium for the exchange of expertise and inspiration, contributions from both smart agriculture and data mining researchers around the world provide foundational insights. The book provides practical application opportunities for the resolution of real-world problems, including contributions from the data mining, data analytics, Edge of Things, and cloud research communities working in the farming production sector. The book offers broad coverage of the concepts, themes, and instruments of this important and evolving area of IOT-based agriculture, Edge of Things and cloud-based farming, Greenhouse IOT, mobile agriculture, sustainable agriculture, and big data analytics in agriculture toward smart farming. - Integrates sustainable agriculture, Greenhouse IOT, precision agriculture, crops monitoring, crops controlling to prediction, livestock monitoring, and farm management - Presents data mining techniques for precision agriculture, including weather prediction, plant disease prediction, and decision support for crop and soil selection - Promotes the importance and uses in managing the agro ecosystem for food security - Emphasizes low energy usage options for low cost and environmental sustainability
Author: Ramesh Chandra Poonia
Publisher: Academic Press
ISBN: 0323903622
Category : Computers
Languages : en
Pages : 408
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Book Description
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
