Proceedings of the 21st EANN (Engineering Applications of Neural Networks) 2020 Conference PDF Download
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Author: Lazaros Iliadis
Publisher: Springer Nature
ISBN: 3030487911
Category : Computers
Languages : en
Pages : 630
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Book Description
This book gathers the proceedings of the 21st Engineering Applications of Neural Networks Conference, which is supported by the International Neural Networks Society (INNS). Artificial Intelligence (AI) has been following a unique course, characterized by alternating growth spurts and “AI winters.” Today, AI is an essential component of the fourth industrial revolution and enjoying its heyday. Further, in specific areas, AI is catching up with or even outperforming human beings. This book offers a comprehensive guide to AI in a variety of areas, concentrating on new or hybrid AI algorithmic approaches with robust applications in diverse sectors. One of the advantages of this book is that it includes robust algorithmic approaches and applications in a broad spectrum of scientific fields, namely the use of convolutional neural networks (CNNs), deep learning and LSTM in robotics/machine vision/engineering/image processing/medical systems/the environment; machine learning and meta learning applied to neurobiological modeling/optimization; state-of-the-art hybrid systems; and the algorithmic foundations of artificial neural networks.
Author: Lazaros Iliadis
Publisher: Springer Nature
ISBN: 3030487911
Category : Computers
Languages : en
Pages : 630
Get Book Here
Book Description
This book gathers the proceedings of the 21st Engineering Applications of Neural Networks Conference, which is supported by the International Neural Networks Society (INNS). Artificial Intelligence (AI) has been following a unique course, characterized by alternating growth spurts and “AI winters.” Today, AI is an essential component of the fourth industrial revolution and enjoying its heyday. Further, in specific areas, AI is catching up with or even outperforming human beings. This book offers a comprehensive guide to AI in a variety of areas, concentrating on new or hybrid AI algorithmic approaches with robust applications in diverse sectors. One of the advantages of this book is that it includes robust algorithmic approaches and applications in a broad spectrum of scientific fields, namely the use of convolutional neural networks (CNNs), deep learning and LSTM in robotics/machine vision/engineering/image processing/medical systems/the environment; machine learning and meta learning applied to neurobiological modeling/optimization; state-of-the-art hybrid systems; and the algorithmic foundations of artificial neural networks.
Author: Pietro Capone
Publisher: Firenze University Press
ISBN:
Category : Architecture
Languages : en
Pages : 1279
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Book Description
Within the overarching theme of “Managing the Digital Transformation of Construction Industry” the 23rd International Conference on Construction Applications of Virtual Reality (CONVR 2023) presented 123 high-quality contributions on the topics of: Virtual and Augmented Reality (VR/AR), Building Information Modeling (BIM), Simulation and Automation, Computer Vision, Data Science, Artificial Intelligence, Linked Data, Semantic Web, Blockchain, Digital Twins, Health & Safety and Construction site management, Green buildings, Occupant-centric design and operation, Internet of Everything. The editors trust that this publication can stimulate and inspire academics, scholars and industry experts in the field, driving innovation, growth and global collaboration among researchers and stakeholders.
Author: Ngoc Thanh Nguyen
Publisher: Springer Nature
ISBN: 3030880818
Category : Computers
Languages : en
Pages : 817
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Book Description
This book constitutes the refereed proceedings of the 13th International Conference on Computational Collective Intelligence, ICCCI 2021, held in September/October 2021. The conference was held virtually due to the COVID-19 pandemic. The 58 full papers were carefully reviewed and selected from 230 submissions. The papers are grouped in topical issues on knowledge engineering and semantic web; social networks and recommender systems; collective decision-making; cooperative strategies for decision making and optimization; data mining and machine learning; computer vision techniques; natural language processing; Internet of Things: technologies and applications; Internet of Things and computational technologies for collective intelligence; computational intelligence for multimedia understanding.
Author: Gupta, Govind P.
Publisher: IGI Global
ISBN: 1668452669
Category : Computers
Languages : en
Pages : 256
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Book Description
Advanced computational intelligence techniques have been designed and developed in recent years to cope with various big data challenges and provide fast and efficient analytics that assist in making critical decisions. With the rapid evolution and development of internet-based services and applications, this technology is receiving attention from researchers, industries, and academic communities and requires additional study. Convergence of Big Data Technologies and Computational Intelligent Techniques considers recent advancements in big data and computational intelligence across fields and disciplines and discusses the various opportunities and challenges of adoption. Covering topics such as deep learning, data mining, smart environments, and high-performance computing, this reference work is crucial for computer scientists, engineers, industry professionals, researchers, scholars, practitioners, academicians, instructors, and students.
Author: Domingo García-Marzá
Publisher: Springer Nature
ISBN: 3031530152
Category :
Languages : en
Pages : 259
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Book Description
Author: Lazaros Iliadis
Publisher: Springer Nature
ISBN: 3030805689
Category : Technology & Engineering
Languages : en
Pages : 521
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Book Description
This book contains the proceedings of the 22nd EANN “Engineering Applications of Neural Networks” 2021 that comprise of research papers on both theoretical foundations and cutting-edge applications of artificial intelligence. Based on the discussed research areas, emphasis is given in advances of machine learning (ML) focusing on the following algorithms-approaches: Augmented ML, autoencoders, adversarial neural networks, blockchain-adaptive methods, convolutional neural networks, deep learning, ensemble methods, learning-federated learning, neural networks, recurrent – long short-term memory. The application domains are related to: Anomaly detection, bio-medical AI, cyber-security, data fusion, e-learning, emotion recognition, environment, hyperspectral imaging, fraud detection, image analysis, inverse kinematics, machine vision, natural language, recommendation systems, robotics, sentiment analysis, simulation, stock market prediction.
Author: Chrisina Jayne
Publisher: Springer
ISBN: 3319441884
Category : Computers
Languages : en
Pages : 365
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Book Description
This book constitutes the refereed proceedings of the 17th International Conference on Engineering Applications of Neural Networks, EANN 2016, held in Aberdeen, UK, in September 2016. The 22 revised full papers and three short papers presented together with two tutorials were carefully reviewed and selected from 41 submissions. The papers are organized in topical sections on active learning and dynamic environments; semi-supervised modeling; classification applications; clustering applications; cyber-physical systems and cloud applications; time-series prediction; learning-algorithms.
Author: Rajeev Tiwari
Publisher: Springer Nature
ISBN: 3031229592
Category : Technology & Engineering
Languages : en
Pages : 247
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Book Description
Increase in consumer awareness of nutritional habits has placed automatic food analysis in the spotlight in recent years. However, food-logging is cumbersome and requires sufficient knowledge of the food item consumed. Additionally, keeping track of every meal can become a tedious task. Accurately documenting dietary caloric intake is crucial to manage weight loss, but also presents challenges because most of the current methods for dietary assessment must rely on memory to recall foods eaten. Food understanding from digital media has become a challenge with important applications in many different domains. Substantial research has demonstrated that digital imaging accurately estimates dietary intake in many environments and it has many advantages over other methods. However, how to derive the food information effectively and efficiently remains a challenging and open research problem. The provided recommendations could be based on calorie counting, healthy food and specific nutritional composition. In addition, if we also consider a system able to log the food consumed by every individual along time, it could provide health-related recommendations in the long-term. Computer Vision specialists have developed new methods for automatic food intake monitoring and food logging. Fourth Industrial Revolution [4.0 IR] technologies such as deep learning and computer vision robotics are key for sustainable food understanding. The need for AI based technologies that allow tracking of physical activities and nutrition habits are rapidly increasing and automatic analysis of food images plays an important role. Computer vision and image processing offers truly impressive advances to various applications like food analytics and healthcare analytics and can aid patients in keeping track of their calorie count easily by automating the calorie counting process. It can inform the user about the number of calories, proteins, carbohydrates, and other nutrients provided by each meal. The information is provided in real-time and thus proves to be an efficient method of nutrition tracking and can be shared with the dietician over the internet, reducing healthcare costs. This is possible by a system made up of, IoT sensors, Cloud-Fog based servers and mobile applications. These systems can generate data or images which can be analyzed using machine learning algorithms. Image Based Computing for Food and Health Analytics covers the current status of food image analysis and presents computer vision and image processing based solutions to enhance and improve the accuracy of current measurements of dietary intake. Many solutions are presented to improve the accuracy of assessment by analyzing health images, data and food industry based images captured by mobile devices. Key technique innovations based on Artificial Intelligence and deep learning-based food image recognition algorithms are also discussed. This book examines the usage of 4.0 industrial revolution technologies such as computer vision and artificial intelligence in the field of healthcare and food industry, providing a comprehensive understanding of computer vision and intelligence methodologies which tackles the main challenges of food and health processing. Additionally, the text focuses on the employing sustainable 4 IR technologies through which consumers can attain the necessary diet and nutrients and can actively monitor their health. In focusing specifically on the food industry and healthcare analytics, it serves as a single source for multidisciplinary information involving AI and vision techniques in the food and health sector. Current advances such as Industry 4.0 and Fog-Cloud based solutions are covered in full, offering readers a fully rounded view of these rapidly advancing health and food analysis systems.
Author: Jagdish Chand Bansal
Publisher: Springer Nature
ISBN: 981993754X
Category : Technology & Engineering
Languages : en
Pages : 215
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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.
Author: Alla G. Kravets
Publisher: Springer Nature
ISBN: 303066077X
Category : Technology & Engineering
Languages : en
Pages : 358
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Book Description
This book highlights original approaches of modelling and intelligent control of cyber-physical systems covering both theoretical and practical aspects. The novel contribution of the book covers the transformation of scientific research and their results into applications for cyber-physical systems design and operation during the whole life cycle in different domains. Given its scope, the book offers an excellent reference book for researchers and other readers in the fields of cyber-physical systems modelling and intelligent control, space exploration and practical implementation of cyber-physical systems. The book also benefits researchers and practitioners in artificial intelligence and machine learning, as described results can be applied in cyber-physical systems design and cost-effectively maintenance. The target audience of this book also includes practitioners and experts, as well as state authorities and representatives of international organizations interested in creating mechanisms for implementing Cyber-Physical Systems projects.
