Advanced Information Networking and Applications, Leonard Barolli; Makoto Takizawa; Fatos Xhafa; Tom
Автор: Rik Das, Siddhartha Bhattacharyya, Sudarshan Nandy Название: Machine Learning Applications: Emerging Trends ISBN: 3110608537 ISBN-13(EAN): 9783110608533 Издательство: Walter de Gruyter Цена: 18586.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
The publication is attempted to address emerging trends in machine learning applications. Recent trends in information identification have identified huge scope in applying machine learning techniques for gaining meaningful insights. Random growth of unstructured data poses new research challenges to handle this huge source of information. Efficient designing of machine learning techniques is the need of the hour. Recent literature in machine learning has emphasized on single technique of information identification. Huge scope exists in developing hybrid machine learning models with reduced computational complexity for enhanced accuracy of information identification. This book will focus on techniques to reduce feature dimension for designing light weight techniques for real time identification and decision fusion. Key Findings of the book will be the use of machine learning in daily lives and the applications of it to improve livelihood. However, it will not be able to cover the entire domain in machine learning in its limited scope. This book is going to benefit the research scholars, entrepreneurs and interdisciplinary approaches to find new ways of applications in machine learning and thus will have novel research contributions. The lightweight techniques can be well used in real time which will add value to practice.
Автор: Siddhartha Bhattacharyya, Vaclav Snasel, Aboul Ella Hassanien, Satadal Saha, B. K. Tripathy Название: Deep Learning: Research and Applications ISBN: 3110670798 ISBN-13(EAN): 9783110670790 Издательство: Walter de Gruyter Цена: 20446.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book will focus on the fundamentals of deep learning along with reporting on the current state-of-art research on deep learning. In addition, it would provide an insight of deep neural networks in action with illustrative coding examples. Moreover, the book will also provide video demonstrations on each chapter. Deep learning is a new area of machine learning research, which has been introduced with the objective of moving ML closer to one of its original goals, i.e. artificial intelligence. Deep learning was developed as an ML approach to deal with complex input-output mappings. While traditional methods successfully solve problems where final value is a simple function of input data, deep learning techniques are able to capture composite relations between non immediately related fields, for example between air pressure recordings and english words, millions of pixels and textual description, brand-related news and future stock prices and almost all real world problems. Deep learning is a class of nature inspired machine learning algorithms that uses a cascade of multiple layers of nonlinear processing units for feature extraction and transformation. Each successive layer uses the output from the previous layer as input. The learning may be supervised (e.g., classification) and/or unsupervised (e.g., pattern analysis) manners. These algorithms learn multiple levels of representations that correspond to different levels of abstraction by resorting to some form of gradient descent for training via backpropagation. Layers that have been used in deep learning include hidden layers of an artificial neural network and sets of propositional formulas. They may also include latent variables organized layer-wise in deep generative models such as the nodes in deep belief networks and deep boltzmann machines. Deep learning is part of state-of-the-art systems in various disciplines, particularly computer vision, automatic speech recognition (ASR) and human action recognition. The unique features of this book include: • tutorials on deep learning framework with focus on tensor flow, keras etc. • video demonstration of each chapter for enabling the readers to have a good understanding of the chapter contents. • a score of worked out examples on real life applications. • illustrative diagrams • coding examples
Автор: MALLICK & BORAH Название: Emerging Trends and Applications in Cognitive Computing ISBN: 1522557938 ISBN-13(EAN): 9781522557937 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 26961.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Though an individual can process a limitless amount of information, the human brain can only comprehend a small amount of data at a time. Using technology can improve the process and comprehension of information, but the technology must learn to behave more like a human brain to employ concepts like memory, learning, visualization ability, and decision making.Emerging Trends and Applications in Cognitive Computing is a fundamental scholarly source that provides empirical studies and theoretical analysis to show how learning methods can solve important application problems throughout various industries and explain how machine learning research is conducted. Including innovative research on topics such as deep neural networks, cyber-physical systems, and pattern recognition, this collection of research will benefit individuals such as IT professionals, academicians, students, researchers, and managers.
Автор: Monica Bianchini; Marco Maggini; Franco Scarselli Название: Innovations in Neural Information Paradigms and Applications ISBN: 3642040020 ISBN-13(EAN): 9783642040023 Издательство: Springer Рейтинг: Цена: 23058.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Presenting the fundamentals and practical applications of neural information systems, this volume presents the recent developments in the field. Self-organizing structures, neural grammar networks and model complexity are among the many topics discussed.
Collaborative Modes on Collaborative Problem Solving.- Modelling Information Flow and Situational Awareness in Wild Fire Response Operations.- Supporting Analytical Reasoning: A study from the automotive industry.- Towards more practical information sharing in disaster situations.- Prototype of Decision Support Based on Estimation of Group Status Using Conversation Analysis.- Preventing Incorrect Opinion Sharing with Weighted Relationship among Agents.- The Temporal Analysis of Network for Community Activity.- Method to Evaluate Difficulty of Technical Terms.- Essential tips for successful collaboration -- a case study of the "Marshmallow challenge.- A mechanism to control aggressive comments in pseudonym type computer mediated communications.- One Size Does Not Fit All: Applying the Right Game Concepts for the Right Persons to Encourage Non-Game Activities.- Gaze-aware Thinking Training Environment to Analyze Internal Self-conversation Process.- Educational Externalization of Thinking Task by Kit-Build Method.- Student authentication method by sequential update of face information registered in e-Learning system.- An Open-ended and Interactive Learning Using Logic Building System with Four-Frame Comic Strip.- Construction of a literature review support system using latent Dirichlet allocation.- Design for Adaptive User Interface for Modeling Students Learning Styles.- An Adaptive Research Support System for Students in Higher Education: Beyond Logging and Tracking.- Investigation of Learning Process with TUI.- A Method for Consensus Building between Teachers and Learners in Higher Education through Co-design Process.- Association Rules on Relationships between Learner's Physiological Information and Mental States During Learning Process.- Listening to Music and Idea Generation.- Application of Co-Creation Design Experiences to the Development of Green Furniture.- Decolonizing Aesthetics: Art with BCI in HCI.- Creation of Shadow Media using Point Cloud and Design of Co-creative Expression Space.- Image mnemonics for cognitive mapping of the museum exhibits.- AR Reference Model for K-Culture Time Machine.- Encouraging People to Interact with Interactive Systems in Public Spaces by Managing Lines of Participants.- Hirose Visualization of composer relationships using implicit data graphs.- Crowd-Cloud Window to the Past: Constructing a Photo Database for On-Site AR Exhibitions by Crowdsourcing.- Backend infrastructure supporting audio augmented reality and storytelling.- Creativity Comes from Interaction: Multi-modal Analyses of Three-creator Communication in Constructing a Lego Castle.- Co-creative Expression Interface: Aiming to Support Embodied Communication for Developmentally Disabled Children.- High-Resolution Tactile Display for Lips.- Fortune Air: Interactive Fortune-Telling for Entertainment Enhancement in a Praying Experience.- Prioritizing Tasks using User-Support-Worker's Activity Model (USWAM).- Improving User Interfaces for a Request Tracking System: Best Practical RT.- Strategic Knowledge Management for Interdisciplinary Teams - Overcoming Barriers of Interdisciplinary Work via an Online Portal Approach.- Data Integration and Knowledge Coordination for Planetary Exploration Traverses.- Gauging the Reliability of Online Health Information in the Turkish Context .- How to Improve Research Data Management - The Case of sciebo (science box).- Well-Being and HCI in Later Life - What Matters?.- Improving Sense of Well-Being by Managing Memories of Experience.- Evaluating Hedonic and Eudaimonic Motives in Human-Computer Interaction.- Personalized Real-Time Sleep Stage from Past Sleep Data to Today's Sleep Estimation.- Exploring Dance Teaching Anxiety in Japanese Schoolteachers.- Sensory Evaluation Method with Multivariate Analysis for Pictograms on Smartphone.- Exploring Information Needs of using Battery Swapping System for Riders.- Detecting Multitasking Work and Negative Routines from Compu
Описание: Computer vision and object recognition are two technological methods that are frequently used in various professional disciplines. In order to maintain high levels of quality and accuracy of services in these sectors, continuous enhancements and improvements are needed. The implementation of artificial intelligence and machine learning has assisted in the development of digital imaging, yet proper research on the applications of these advancing technologies is lacking.
Applications of Advanced Machine Intelligence in Computer Vision and Object Recognition: Emerging Research and Opportunities explores the theoretical and practical aspects of modern advancements in digital image analysis and object detection as well as its applications within healthcare, security, and engineering fields. Featuring coverage on a broad range of topics such as disease detection, adaptive learning, and automated image segmentation, this book is ideally designed for engineers, physicians, researchers, academicians, practitioners, scientists, industry professionals, scholars, and students seeking research on the current developments in object recognition using artificial intelligence.
Описание: Computer vision and object recognition are two technological methods that are frequently used in various professional disciplines. In order to maintain high levels of quality and accuracy of services in these sectors, continuous enhancements and improvements are needed. The implementation of artificial intelligence and machine learning has assisted in the development of digital imaging, yet proper research on the applications of these advancing technologies is lacking.
Applications of Advanced Machine Intelligence in Computer Vision and Object Recognition: Emerging Research and Opportunities explores the theoretical and practical aspects of modern advancements in digital image analysis and object detection as well as its applications within healthcare, security, and engineering fields. Featuring coverage on a broad range of topics such as disease detection, adaptive learning, and automated image segmentation, this book is ideally designed for engineers, physicians, researchers, academicians, practitioners, scientists, industry professionals, scholars, and students seeking research on the current developments in object recognition using artificial intelligence.
ООО "Логосфера " Тел:+7(495) 980-12-10 www.logobook.ru
