Computer Vision and Machine Learning in Agriculture, Volume 2

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Publisher : Springer Nature
ISBN 13 : 9811699917
Total Pages : 269 pages
Book Rating : 4.8/5 (116 download)

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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.

Computer Vision and Machine Learning in Agriculture, Volume 3

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Publisher : Springer Nature
ISBN 13 : 981993754X
Total Pages : 215 pages
Book Rating : 4.8/5 (199 download)

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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.

Computer Vision and Machine Learning in Agriculture

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Publisher :
ISBN 13 : 9789813364257
Total Pages : 0 pages
Book Rating : 4.3/5 (642 download)

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Book Synopsis Computer Vision and Machine Learning in Agriculture by : Mohammad Shorif Uddin

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.

Artificial Intelligence in Agriculture

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Publisher : CRC Press
ISBN 13 : 1000506215
Total Pages : 186 pages
Book Rating : 4.0/5 (5 download)

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Book Synopsis Artificial Intelligence in Agriculture by : Rajesh Singh

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.

Artificial Intelligence for Biology and Agriculture

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Publisher : Springer Science & Business Media
ISBN 13 : 9401150486
Total Pages : 258 pages
Book Rating : 4.4/5 (11 download)

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Book Synopsis Artificial Intelligence for Biology and Agriculture by : S. Panigrahi

Download or read book Artificial Intelligence for Biology and Agriculture written by S. Panigrahi and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Application of Machine Learning in Agriculture

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Publisher : Academic Press
ISBN 13 : 0323906680
Total Pages : 332 pages
Book Rating : 4.3/5 (239 download)

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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

Applications of Computer Vision and Drone Technology in Agriculture 4.0

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Author :
Publisher : Springer Nature
ISBN 13 : 9819986842
Total Pages : 332 pages
Book Rating : 4.8/5 (199 download)

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Book Synopsis Applications of Computer Vision and Drone Technology in Agriculture 4.0 by : Siddharth Singh Chouhan

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:

Internet of Things and Machine Learning in Agriculture

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Publisher : Walter de Gruyter GmbH & Co KG
ISBN 13 : 3110691280
Total Pages : 454 pages
Book Rating : 4.1/5 (16 download)

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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.

Machine Vision and Machine Learning for Plant Phenotyping and Precision Agriculture

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Publisher : Frontiers Media SA
ISBN 13 : 283254293X
Total Pages : 423 pages
Book Rating : 4.8/5 (325 download)

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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.

Machine Learning and Deep Learning for Smart Agriculture and Applications

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Publisher : IGI Global
ISBN 13 : 1668499762
Total Pages : 276 pages
Book Rating : 4.6/5 (684 download)

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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.

Computer vision in plant phenotyping and agriculture

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Publisher : Frontiers Media SA
ISBN 13 : 2832510655
Total Pages : 265 pages
Book Rating : 4.8/5 (325 download)

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Book Synopsis Computer vision in plant phenotyping and agriculture by : Valerio Giuffrida

Download or read book Computer vision in plant phenotyping and agriculture written by Valerio Giuffrida and published by Frontiers Media SA. This book was released on 2023-06-06 with total page 265 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Applications of Computer Vision and Drone Technology in Agriculture 4.0

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Publisher : Springer
ISBN 13 : 9789819986835
Total Pages : 0 pages
Book Rating : 4.9/5 (868 download)

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Book Synopsis Applications of Computer Vision and Drone Technology in Agriculture 4.0 by : Siddharth Singh Chouhan

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.

Recent Advances in Big Data, Machine, and Deep Learning for Precision Agriculture

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Publisher : Frontiers Media SA
ISBN 13 : 2832544959
Total Pages : 379 pages
Book Rating : 4.8/5 (325 download)

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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:

Applications of Image Processing and Soft Computing Systems in Agriculture

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Publisher : IGI Global
ISBN 13 : 152258028X
Total Pages : 337 pages
Book Rating : 4.5/5 (225 download)

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Book Synopsis Applications of Image Processing and Soft Computing Systems in Agriculture by : Razmjooy, Navid

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.

Computer Vision-Based Agriculture Engineering

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Publisher : CRC Press
ISBN 13 : 1000691616
Total Pages : 330 pages
Book Rating : 4.0/5 (6 download)

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Book Synopsis Computer Vision-Based Agriculture Engineering by : Han Zhongzhi

Download or read book Computer Vision-Based Agriculture Engineering written by Han Zhongzhi and published by CRC Press. This book was released on 2019-09-16 with total page 330 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Deep Learning for Agricultural Visual Perception

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Publisher : Springer Nature
ISBN 13 : 9819949734
Total Pages : 140 pages
Book Rating : 4.8/5 (199 download)

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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.

Artificial Intelligence-of-Things (AIoT) in Precision Agriculture

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Author :
Publisher : Frontiers Media SA
ISBN 13 : 2832544312
Total Pages : 206 pages
Book Rating : 4.8/5 (325 download)

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Book Synopsis Artificial Intelligence-of-Things (AIoT) in Precision Agriculture by : Yaqoob Majeed

Download or read book Artificial Intelligence-of-Things (AIoT) in Precision Agriculture written by Yaqoob Majeed and published by Frontiers Media SA. This book was released on 2024-02-12 with total page 206 pages. Available in PDF, EPUB and Kindle. Book excerpt: The merging of Artificial Intelligence (AI) and Internet-of-Things is known as Artificial Intelligence-of-Things (AIoT). IoT consists of interlinked computing devices and machines which can acquire, transfer, and execute field/industrial operations without human involvement, while AI processes the acquired data and helps extract the required information. The technologies work in synergy: AI enriches IoT through machine learning and deep learning-based data analysis and learning capabilities, whereas IoT enriches AI through data acquisition, connectivity, and data exchange. Precision agriculture is becoming critically important for sustainable food production to meet the growing food demand. In recent decades, AI and IoT techniques have played an increasing role within industrial operations (e.g. autonomous manufacturing, automated supply chain management, predictive maintenance, smart energy grids, smart home appliances, and wearables), however, agricultural field operations are still heavily dependent on human labor. This is because these operations are ill-defined, unstructured, and susceptible to variation in natural conditions (e.g. illumination, landscape, atmosphere) plus the biological nature of crops (fruits, stems, leaves, and/or shoots continuously change their shape and/or color as they grow).