Applications of Image Processing and Soft Computing Systems in Agriculture


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.




Computer Vision and Machine Learning in Agriculture, Volume 2


Book Description

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.




Applications of Remote Image Capture System in Agriculture


Book Description

Remote image capture systems are a key element in efficient and sustainable agriculture nowadays. They are increasingly being used to obtain information of interest from the crops, the soil and the environment. It includes different types of capturing devices: from satellites and drones, to in-field devices; different types of spectral information, from visible RGB images, to multispectral images; different types of applications; and different types of techniques in the areas of image processing, computer vision, pattern recognition and machine learning. This book covers all these aspects, through a series of chapters that describe specific recent applications of these techniques in interesting problems of agricultural engineering.




Image Processing in Agriculture and Forestry


Book Description

This book is a printed edition of the Special Issue "Image Processing in Agriculture and Forestry" that was published in J. Imaging




Soft Computing and Optimization Techniques for Sustainable Agriculture


Book Description

This book covers the emerging applications of different computational and optimization techniques in order to achieve a sustainable agriculture. A sustainable agricultural management requires tools in providing integrated, area-specifi c, and interpreted prediction or forecasting and guidance in every aspect in agriculture.




Precision Agriculture for Sustainability


Book Description

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.




Computer Vision and Machine Learning in Agriculture, Volume 3


Book Description

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.




Information and Communication Technologies for Agriculture—Theme II: Data


Book Description

This volume is the second (II) of four under the main themes of Digitizing Agriculture and Information and Communication Technologies (ICT). The four volumes cover rapidly developing processes including Sensors (I), Data (II), Decision (III), and Actions (IV). Volumes are related to ‘digital transformation” within agricultural production and provision systems, and in the context of Smart Farming Technology and Knowledge-based Agriculture. Content spans broadly from data mining and visualization to big data analytics and decision making, alongside with the sustainability aspects stemming from the digital transformation of farming. The four volumes comprise the outcome of the 12th EFITA Congress, also incorporating chapters that originated from select presentations of the Congress. The first part of this book (II) focuses on data technologies in relation to agriculture and presents three key points in data management, namely, data collection, data fusion, and their uses in machine learning and artificial intelligent technologies. Part 2 is devoted to the integration of these technologies in agricultural production processes by presenting specific applications in the domain. Part 3 examines the added value of data management within agricultural products value chain. The book provides an exceptional reference for those researching and working in or adjacent to agricultural production, including engineers in machine learning and AI, operations management, decision analysis, information analysis, to name just a few. Specific advances covered in the volume: Big data management from heterogenous sources Data mining within large data sets Data fusion and visualization IoT based management systems Data Knowledge Management for converting data into valuable information Metadata and data standards for expanding knowledge through different data platforms AI - based image processing for agricultural systems Data - based agricultural business Machine learning application in agricultural products value chain







Trends and Advancements of Image Processing and Its Applications


Book Description

This book covers current technological innovations and applications in image processing, introducing analysis techniques and describing applications in remote sensing and manufacturing, among others. The authors include new concepts of color space transformation like color interpolation, among others. Also, the concept of Shearlet Transform and Wavelet Transform and their implementation are discussed. The authors include a perspective about concepts and techniques of remote sensing like image mining, geographical, and agricultural resources. The book also includes several applications of human organ biomedical image analysis. In addition, the principle of moving object detection and tracking — including recent trends in moving vehicles and ship detection – is described. Presents developments of current research in various areas of image processing; Includes applications of image processing in remote sensing, astronomy, and manufacturing; Pertains to researchers, academics, students, and practitioners in image processing.