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Robots and autonomous machines for agriculture production
In recent years, due to the improved performance of artificial intelligence, precision agriculture, and advanced control, they have been widely used in various agricultural applications, including management, disease detection, crop monitoring, yield estimation, and crop harvesting. Robotics and autonomous machines represent a high-level application of automation in agriculture, based on precise and resource-efficient approaches to sustainably achieve greater efficiency and quality in the production of agricultural products while reducing environmental impact. Reactive technologies based on agricultural robots and autonomous machines are separate but closely related fields covering the application of automated control and robotic platforms at all levels of agricultural production. In robotic or autonomous systems, agricultural sensing and control is particularly difficult due to the complexity of the environment in which agricultural production operates.
Robotics and Rehabilitation Intelligence ; 1st International Conference, ICRRI 2020, Fushun, China, September 9–11, 2020, Proceedings, Part II
This 2-volume set constitutes the refereed proceedings of 1st International Conference on Robotics and Rehabilitation Intelligence, ICRRI 2020, held in Fushun, China, in September 2020. The 56 full and 4 short papers were carefully reviewed and selected from 188 submissions. The papers are divided into the following topical sections. In the first volume: Rehabilitation robotics and safety; machine vision application; electric drive and power system fault diagnosis; robust stability and stabilization; intelligent method application; intelligent control and perception; smart remanufacturing and industrial intelligence; and intelligent control of integrated energy system. In the second volume: smart healthcare and intelligent information processing; human-robot interaction; multi-robot systems and control; robot design and control; robotic vision and machine intelligence; optimization method in monitoring; advanced process control in petrochemical process; and rehabilitation intelligence.
Robotics and Rehabilitation Intelligence ; 1st International Conference, ICRRI 2020, Fushun, China, September 9–11, 2020, Proceedings, Part I
This 2-volume set constitutes the refereed proceedings of 1st International Conference on Robotics and Rehabilitation Intelligence, ICRRI 2020, held in Fushun, China, in September 2020. The 56 full and 4 short papers were carefully reviewed and selected from 188 submissions. The papers are divided into the following topical sections. In the first volume: Rehabilitation robotics and safety; machine vision application; electric drive and power system fault diagnosis; robust stability and stabilization; intelligent method application; intelligent control and perception; smart remanufacturing and industrial intelligence; and intelligent control of integrated energy system. In the second volume: smart healthcare and intelligent information processing; human-robot interaction; multi-robot systems and control; robot design and control; robotic vision and machine intelligence; optimization method in monitoring; advanced process control in petrochemical process; and rehabilitation intelligence.
RoboCup 2007 : Robot Soccer World Cup XI
The book presented at the symposium focused on topics related to these three events and to artificial intelligence and robotics in general.The book provides a valuable source of reference and inspiration for R&D professionals and educationalists active or interested in robotics and artificial intelligence.
RoboCup 2005 : Robot Soccer World Cup IX
This book constitutes the ninth official archival publication devoted to RoboCup, documenting presentations at the RoboCup 2005 International Symposium, held in Osaka, Japan, July 2005 alongside the RoboCup Competition. The book presents 34 revised full papers and 38 revised short papers together with two award-winning papers. This is a valuable source of reference and inspiration for those interested in robotics or distributed intelligence, and mandatory reading for the rapidly growing RoboCup community.
Revolutionary applications of intelligent drones
Includes details starting from the basics of drone technology and discusses diverse aspects related to drone designing and implementation. Further chapters detail the impact of drone technology on society in terms of development, challenges, and security concerns. Then, implementations of artificial intelligence techniques such as machine learning, deep learning, etc., are discussed to translate drone technology into intelligent drone technology. There are diverse applications in the area of intelligent drone technologies such as agriculture, disaster management, security, military, etc. Hence, in this book, some of the drone-specific applications are discussed.
Research and Development in Intelligent Systems XXIV ; Proceedings of AI-2007, the 27th SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence
They present new and innovative developments in the field, divided into sections on Constraint Satisfaction, AI Techniques, Data Mining and Machine Learning, Multi-Agent Systems, Data Mining, and Knowledge Acquisition and Management.
ReRAM-Based Machine Learning
The transition towards exascale computing has resulted in major transformations in computing paradigms. The need to analyze and respond to such large amounts of data sets has led to the adoption of machine learning (ML) and deep learning (DL) methods in a wide range of applications. One of the major challenges is the fetching of data from computing memory and writing it back without experiencing a memory-wall bottleneck. To address such concerns, in-memory computing (IMC) and supporting frameworks have been introduced. In-memory computing methods have ultra-low power and high-density embedded storage. Resistive Random-Access Memory (ReRAM) technology seems the most promising IMC solution due to its minimized leakage power, reduced power consumption and smaller hardware footprint, as well as its compatibility with CMOS technology, which is widely used in industry. Introduce ReRAM techniques for performing distributed computing using IMC accelerators, present ReRAM-based IMC architectures that can perform computations of ML and data-intensive applications, as well as strategies to map ML designs onto hardware accelerators.
Representation learning for natural language processing
Provides an overview of the recent advances in representation learning theory, algorithms, and applications for natural language processing (NLP), ranging from word embeddings to pre-trained language models. It is divided into four parts. Part I presents the representation learning techniques for multiple language entries, including words, sentences and documents, as well as pre-training techniques. Part II then introduces the related representation techniques to NLP, including graphs, cross-modal entries, and robustness. Part III then introduces the representation techniques for the knowledge that are closely related to NLP, including entity-based world knowledge, sememe-based linguistic knowledge, legal domain knowledge and biomedical domain knowledge. Lastly, Part IV discusses the remaining challenges and future research directions..
Representation Learning for Natural Language Processing
This book provides an overview of the recent advances in representation learning theory, algorithms and applications for natural language processing (NLP). It is divided into three parts.
Representation Learning : Propositionalization and Embeddings
This monograph addresses advances in representation learning, a cutting-edge research area of machine learning. Representation learning refers to modern data transformation techniques that convert data of different modalities and complexity, including texts, graphs, and relations, into compact tabular representations, which effectively capture their semantic properties and relations. The monograph focuses on (i) propositionalization approaches, established in relational learning and inductive logic programming, and (ii) embedding approaches, which have gained popularity with recent advances in deep learning. The authors establish a unifying perspective on representation learning techniques developed in these various areas of modern data science, enabling the reader to understand the common underlying principles and to gain insight using selected examples and sample Python code. The monograph should be of interest to a wide audience, ranging from data scientists, machine learning researchers and students to developers, software engineers and industrial researchers interested in hands-on AI solutions.
Reliable Face Recognition Methods : System Design, Implementation and Evaluation
This book seeks to comprehensively address the face recognition problem while gaining new insights from complementary fields of endeavor. The book examines the evolution of research surrounding the field to date, explores new directions, and offers specific guidance on the most promising venues for future research and development.
Regularized system identification: learning dynamic models from data
Provides a comprehensive treatment of recent developments in kernel-based identification that are of interest to anyone engaged in learning dynamic systems from data. The reader is led step by step into understanding of a novel paradigm that leverages the power of machine learning without losing sight of the system-theoretical principles of black-box identification. The authors’ reformulation of the identification problem in the light of regularization theory not only offers new insight on classical questions, but paves the way to new and powerful algorithms for a variety of linear and nonlinear problems. Regression methods such as regularization networks and support vector machines are the basis of techniques that extend the function-estimation problem to the estimation of dynamic models. Many examples, also from real-world applications, illustrate the comparative advantages of the new nonparametric approach with respect to classic parametric prediction error methods.
Recent Challenges in Intelligent Information and Database Systems ; 13th Asian Conference, ACIIDS 2021, Phuket, Thailand, April 7–10, 2021, Proceedings
This volume constitutes the refereed proceedings of the 13th Asian Conference on Intelligent Information and Database Systems, ACIIDS 2021, held in Phuket, Thailand, in April 2021. The total of 35 full papers accepted for publication in these proceedings were carefully reviewed and selected from 291 submissions. The papers are organized in the following topical sections: data mining and machine learning methods; advanced data mining techniques and applications; intelligent and contextual systems; natural language processing; network systems and applications; computational imaging and vision; decision support and control systems; data modelling and processing for Industry 4.0.
Recent advances in robotics and intelligent robots applications
Research in robotics has witnessed a transformative evolution over the past decade, driven by unprecedented advancements in artificial intelligence, machine learning, and material science. This reprint, "Recent Advances in Robotics and Intelligent Robot Applications", aims to provide a comprehensive overview of the latest research and developments that are shaping future robotics research in corresponding areas.
Recent Advances in Reinforcement Learning ; 8th European Workshop, EWRL 2008, Villeneuve d’Ascq, France, June 30-July 3, 2008, Revised and Selected Papers
They are dedicated to the field of and current researches in reinforcement learning.There was an air of excitement as substantial progress was reported in many areas including Computer Go, robotics, and fitted methods.
Recent advances in machine learning and computational intelligence
Machine learning and computational intelligence have been applied to various areas and witnessed many successes. The research in this publication explorse many intelligent algorithms which are characterized by computational adaptability, robustness, and high performance. These algorithms facilitate intelligent behavior in complex and dynamic environments and the development of technology that enables machines to think, behave, or act in a more humanesque fashion. This reprint aims to present and discuss the most recent innovations, trends, concerns, challenges, solutions, and application fields in the areas of machine learning and computational intelligence.
Radiation effects of advanced electronic devices and circuits
Aims to disclose the basic mechanisms of radiation effects for advanced devices and the breakthrough of new solutions to assess and mitigate radiation sensitivity in advanced devices and integrated circuits. This reprint presents new modeling approaches that predict how radiation impacts electronic devices and circuits. Accurate models are essential for designing devices that can tolerate radiation without significant performance degradation. We also focus on the innovative design and fabrication techniques that enhance the radiation tolerance of integrated circuits. Moreover, some discussions highlight new testing protocols and methodologies that provide more accurate and comprehensive evaluations of radiation hardness, as well as the latest advancements and trends that are of particular interest to researchers and professionals in the radiation effects community.
Quantum machine learning = التعلم الالي الكمومي
"Quantum Med + " A mobile application offers a comprehensive suite of medical services, encompassing knowledge sharing, social interaction, and advanced diagnostics. One of the unique features of this system is the integration of quantum technologies for Lung tumor and brain tumors. The application provides a range of health services Three AI models respectively include detecting a brain tumor through MRI images, checking for lung cancer, and helping laboratory experts identify the tumor if it is malignant or benign. In addition to a range of services such as providing medical books and practical articles in the medical field and the possibility of the user to create a post to ask about a health condition or request help By combining these elements, the system aims to revolutionize the way medical services are accessed and delivered, ultimately improving healthcare outcomes for users.
Quality of information and communications technology ; 13th International Conference, QUATIC 2020, Faro, Portugal, September 9–11, 2020, Proceedings
This book constitutes the refereed proceedings of the 13th International Conference on the Quality of Information and Communications Technology, QUATIC 2020, held in Faro, Portugal*, in September 2020. The 27 full papers and 12 short papers were carefully reviewed and selected from 81 submissions. The papers are organized in topical sections: quality aspects in machine learning, AI and data analytics; evidence-based software quality engineering; human and artificial intelligences for software evolution; process modeling, improvement and assessment; software quality education and training; quality aspects in quantum computing; safety, security and privacy; ICT verification and validation; RE, MDD and agile.
