LoveReading

Becoming a member of the LoveReading community is free.

No catches, no fine print just unadulterated book loving, with your favourite books saved to your own digital bookshelf.

New members get entered into our monthly draw to win £100 to spend in your local bookshop Plus lots lots more…

Find out more

Artificial intelligence

See below for a selection of the latest books from Artificial intelligence category. Presented with a red border are the Artificial intelligence books that have been lovingly read and reviewed by the experts at Lovereading. With expert reading recommendations made by people with a passion for books and some unique features Lovereading will help you find great Artificial intelligence books and those from many more genres to read that will keep you inspired and entertained. And it's all free!

AI on Trial

AI on Trial

Author: Mark Deem, Peter Warren Format: Paperback / softback Release Date: 31/10/2020

With AI now being used in many walks of our every day life, this book looks at the questions surrounding AI and its future. For example: Who owns AI? Is AI a product in its own right? Should AI have rights and responsibilities? What are the status, capacity and authority issues relating to AI? Is AI racist? What are the issues (legal and ethical) created by implicit bias of coders and data sets? Can AI be used to gain a competitive advantage? If so, is it anti-competitive? What is the role of AI in cybersecurity? Can we trust AI? Written by experts and laid out in the style of a trial, starting with opening submissions, followed by the evidence, closing submissions and finally the judgment, the book takes an innovative approach to the most innovative of technological areas.

Democratization of Expertise

Democratization of Expertise

Author: Ron (University of South Carolina Upstate, SC, USA) Fulbright Format: Hardback Release Date: 30/10/2020

We create technology enabling us to do things never before possible and it ultimately changes the way we live, work, play, and interact with each other. Throughout human history, the democratization of technology making a technology available to the masses, has brought about sweeping cultural, social, political, and societal changes. In the last half-century, the democratization of computers, information, the Internet, and social media have revolutionized and transformed our lives. We now stand at the beginning of a new era sure to bring about waves of new revolutions, the cognitive systems era. Until now, humans have done all of the thinking. However, our lives are about to be infused with artificial entities capable of performing high-level cognitive processing previously possible only in the human mind. Systems capable of this kind of synthetic cognition will achieve and surpass the level of human experts in almost every field of endeavor. Far from replacing humans, these cognitive systems will be our collaborators, teachers, confidants, colleagues, and companions. The future will belong to those who can better partner with these cognitive systems. Made available to the average person via the Internet, handheld devices, and through ordinary objects all around us, expertise will become democratized. Everything will change when anyone has access to expertise in any field and new things will be possible. The democratization of expertise is the foundation on which our society's revolutions will be built over the next half-century. This book discusses societal and cultural revolutions throughout history brought about by the adoption of new technology and gives brief histories of human cognitive augmentation and artificial intelligence. In the coming cognitive systems era, humans, by collaboratively partnering with cognitive systems, will together achieve expert-level performance-synthetic expertise-with humans performing some of the cognitive processing and cognitive systems performing some. As the capabilities of cognitive systems improve over time, the balance of thinking will shift from being mostly human to mostly artificial. This book introduces the Levels of Cognitive Augmentation to describe this shift. Drawing from previous research in cognitive systems and intelligent agent theory, the knowledge stores required for expertise are identified in a Knowledge Level description of expertise. This book introduces a new abstract level, called the Expertise Level to describe the skills needed for expertise. Combining the knowledge-level and expertise-level descriptions, this book introduces the Model of Expertise. This book demonstrates use of the Model of Expertise by presenting several synthetic expert architectures: a synthetic teacher (Synthia), a synthetic friend/therapist (Sy), a synthetic elderly companion (Lois), a synthetic research companion (Synclair), and an automated scientific hypothesis explorer (Ashe). This book is intended for anyone interested in the fields of cognitive systems, cognitive computing, cognitive augmentation, or artificial intelligence or the impact of technologies from these fields on society. Anyone doing research and development in the area of cognitive systems or artificial intelligence will find this book particularly useful.

Democratization of Expertise

Democratization of Expertise

Author: Ron (University of South Carolina Upstate, SC, USA) Fulbright Format: Paperback / softback Release Date: 30/10/2020

We create technology enabling us to do things never before possible and it ultimately changes the way we live, work, play, and interact with each other. Throughout human history, the democratization of technology making a technology available to the masses, has brought about sweeping cultural, social, political, and societal changes. In the last half-century, the democratization of computers, information, the Internet, and social media have revolutionized and transformed our lives. We now stand at the beginning of a new era sure to bring about waves of new revolutions, the cognitive systems era. Until now, humans have done all of the thinking. However, our lives are about to be infused with artificial entities capable of performing high-level cognitive processing previously possible only in the human mind. Systems capable of this kind of synthetic cognition will achieve and surpass the level of human experts in almost every field of endeavor. Far from replacing humans, these cognitive systems will be our collaborators, teachers, confidants, colleagues, and companions. The future will belong to those who can better partner with these cognitive systems. Made available to the average person via the Internet, handheld devices, and through ordinary objects all around us, expertise will become democratized. Everything will change when anyone has access to expertise in any field and new things will be possible. The democratization of expertise is the foundation on which our society's revolutions will be built over the next half-century. This book discusses societal and cultural revolutions throughout history brought about by the adoption of new technology and gives brief histories of human cognitive augmentation and artificial intelligence. In the coming cognitive systems era, humans, by collaboratively partnering with cognitive systems, will together achieve expert-level performance-synthetic expertise-with humans performing some of the cognitive processing and cognitive systems performing some. As the capabilities of cognitive systems improve over time, the balance of thinking will shift from being mostly human to mostly artificial. This book introduces the Levels of Cognitive Augmentation to describe this shift. Drawing from previous research in cognitive systems and intelligent agent theory, the knowledge stores required for expertise are identified in a Knowledge Level description of expertise. This book introduces a new abstract level, called the Expertise Level to describe the skills needed for expertise. Combining the knowledge-level and expertise-level descriptions, this book introduces the Model of Expertise. This book demonstrates use of the Model of Expertise by presenting several synthetic expert architectures: a synthetic teacher (Synthia), a synthetic friend/therapist (Sy), a synthetic elderly companion (Lois), a synthetic research companion (Synclair), and an automated scientific hypothesis explorer (Ashe). This book is intended for anyone interested in the fields of cognitive systems, cognitive computing, cognitive augmentation, or artificial intelligence or the impact of technologies from these fields on society. Anyone doing research and development in the area of cognitive systems or artificial intelligence will find this book particularly useful.

Machine Learning and Big Data

Machine Learning and Big Data

Author: Uma N. Dulhare, Khaleel Ahmad, Khairol Amali Bin Ahmad Format: Hardback Release Date: 29/10/2020

Currently many different application areas for Big Data (BD) and Machine Learning (ML) are being explored. These promising application areas for BD/ML are the social sites, search engines, multimedia sharing sites, various stock exchange sites, online gaming, online survey sites and various news sites, and so on. To date, various use-cases for this application area are being researched and developed. Software applications are already being published and used in various settings from education and training to discover useful hidden patterns and other information like customer choices and market trends that can help organizations make more informed and customer-oriented business decisions. Combining BD with ML will provide powerful, largely unexplored application areas that will revolutionize practice in Videos Surveillance, Social Media Services, Email Spam and Malware Filtering, Online Fraud Detection, and so on. It is very important to continuously monitor and understand these effects from safety and societal point of view. Hence, the main purpose of this book is for researchers, software developers and practitioners, academicians and students to showcase novel use-cases and applications, present empirical research results from user-centered qualitative and quantitative experiments of these new applications, and facilitate a discussion forum to explore the latest trends in big data and machine learning by providing algorithms which can be trained to perform interdisciplinary techniques such as statistics, linear algebra, and optimization and also create automated systems that can sift through large volumes of data at high speed to make predictions or decisions without human intervention

Deep Learning

Deep Learning

Author: Andrew Glassner Format: Hardback Release Date: 29/10/2020

AI in Manufacturing and Green Technology

AI in Manufacturing and Green Technology

This book focuses on making the environment sustainable by employing engineering aspects and green computing through concepts of modern education and solutions. It visualizes the potential of artificial intelligence in manufacturing and green technology, enhanced by business activities and strategies for rapid implementation. This book covers the usages of renewable resources, covers the implementation of the latest energy generation technology, discusses resources not depleted in nature, illustrates the facilitation towards growth of green technology in industry, and offers the usage of advanced materials. The book also covers environmental sustainability and the current trends in manufacturing. The book provides basic concepts of green technology along with the technology aspects for researchers, faculty, and students.

Content-Based Image Classification

Content-Based Image Classification

Author: Rik Das Format: Hardback Release Date: 20/10/2020

Content-Based Image Classification Efficient Machine Learning using Robust Feature Extraction Techniques is a comprehensive guide to initiate and excel in researching with invaluable image data. Social Science Research Network has revealed the fact that sixty five percent of us are visual learners. Research data provided by Hyerle(2000) has clearly shown ninety percent of information in our brain is visual. Thus, it is no wonder that processing of visual information in brain is 60,000 times faster than text based information (3M Corporation, 2001). Recent times have witnessed significant surge in conversing with images with popularity of social networking platforms. The other reason of embracing extensive usage of image data is easy availability of image capturing devices in the form of high resolution cell phone cameras. Extensive application of image data in diversified application areas including, medical science, media, sports, remote sensing and so on has stimulated the requirement of further research in optimizing archival, maintenance and retrieval of appropriate image content to leverage data driven decision making. This book has demonstrated several techniques of image processing to represent image data in desired format for information identification. It has discussed the application of machine learning and deep learning for identifying and categorizing appropriate image data helpful in designing automated decision support systems. The book offers comprehensive coverage of the most essential topics, including: Different Open Access Image Datasets to start your Machine Learning Journey Image Feature Extraction with Novel Handcrafted Techniques (Traditional Feature Extraction) Image Feature Extraction with Automated Techniques (Representation Learning with CNNs) Significance of Fusion Based Approaches in enhancing Classification Accuracy Matlab Codes for implementing the Techniques Use of Open Access Data Mining tool Weka for multiple tasks The book is intended for budding researchers, technocrats, engineering students and machine learning / deep learning enthusiasts who are willing to start their computer vision journey with content based image recognition. The readers will get a clear picture of the essentials for transforming the image data into valuable means of insight generation. The book will make the reader adept with coding tricks necessary to propose novel mechanisms and also to enhance state-of-the-art with disruptive approaches. The Weka guide provided in the book can prove itself beneficial for those who are not comfortable with coding for application of machine learning algorithm. The Weka tool will assist the learner to implement machine learning algorithms with the click of a button. Thus, the book is going to be your stepping stone for your machine learning journey. You may visit the author's website to get in touch for any further guidance required (Website: https://www.rikdas.com/)

Computational Models for Cognitive Vision

Computational Models for Cognitive Vision

Author: Hiranmay Ghosh Format: Paperback / softback Release Date: 15/10/2020

Learn how to apply cognitive principles to the problems of computer vision Computational Models for Cognitive Vision formulates the computational models for the cognitive principles found in biological vision, and applies those models to computer vision tasks. Such principles include perceptual grouping, attention, visual quality and aesthetics, knowledge-based interpretation and learning, to name a few. The author's ultimate goal is to provide a framework for creation of a machine vision system with the capability and versatility of the human vision. Written by Dr. Hiranmay Ghosh, the book takes readers through the basic principles and the computational models for cognitive vision, Bayesian reasoning for perception and cognition, and other related topics, before establishing the relationship of cognitive vision with the multi-disciplinary field broadly referred to as artificial intelligence . The principles are illustrated with diverse application examples in computer vision, such as computational photography, digital heritage and social robots. The author concludes with suggestions for future research and salient observations about the state of the field of cognitive vision. Other topics covered in the book include: - knowledge representation techniques - evolution of cognitive architectures - deep learning approaches for visual cognition Undergraduate students, graduate students, engineers, and researchers interested in cognitive vision will consider this an indispensable and practical resource in the development and study of computer vision.

Soft Computing Applications and Techniques in Healthcare

Soft Computing Applications and Techniques in Healthcare

Author: Ashish (Gyan Ganga Institute of Technology and Sciences, India) Mishra Format: Hardback Release Date: 15/10/2020

This book provides insights into contemporary issues and challenges in soft computing applications and techniques in healthcare. It will be a useful guide to identify, categorise and assess the role of different soft computing techniques for disease, diagnosis and prediction due to technological advancements. The book explores applications in soft computing and covers empirical properties of artificial neural network (ANN), evolutionary computing, fuzzy logic and statistical techniques. It presents basic and advanced concepts to help beginners and industry professionals get up to speed on the latest developments in soft computing and healthcare systems. It incorporates the latest methodologies and challenges facing soft computing, examines descriptive, predictive and social network techniques and discusses analytics tools and their role in providing effective solutions for science and technology. The primary users for the book include researchers, academicians, postgraduate students, specialists and practitioners. Dr. Ashish Mishra is a professor in the Department of Computer Science and Engineering, Gyan Ganga Institute of Technology and Sciences, Jabalpur (M.P), India. He is also a reviewer and Session Chair of IEEE international conferences, CSNT-2015, CICN-2016, CICN2017, INDIACom-2019 ICICC-CONF 2019 and ICTIDS 2019. His research interests include IOT, data mining, cloud computing, image processing, knowledge-based systems and artificial intelligence. He has published nine patents in Intellectual Property in India. He has published four books in the area of data mining, image processing and latex. Dr. G. Suseendran is an assistant professor in the Department of Information Technology, School of Computing Sciences, Vels Institute of Science, Technology and Advanced Studies (VISTAS), Chennai, Tamil Nadu, India. His research interests include ad-hoc networks, IOT, data mining, cloud computing, image processing, knowledge-based systems and web information exploration. He serves as International Committee Member for international conferences conducted in association with IEEE, Springer and Scopus. He has published more than 60 research papers in various international journals, including Science Citation Index, Scopus, IEEE Access and University Grants Commission of India-approved journals. He has presented 20 papers in various international conferences. Prof. Trung-Nghia Phung was Dean of Faculty of Electronics and Telecommunications, Thai Nguyen University of Information and Communication Technology (ICTU), Thai Nguyen, Vietnam. He is currently an associate professor and head of Academic Affairs, ICTU. He has published more than 60 research papers. He was the recipient of the award for the excellent young researcher (Golden Globe Award) from Ministry of Science and Technology of Vietnam in 2008. His main research interests include speech, audio and biomedical signal processing. He was a co-chair of the International Conference on Advances in Information and Communication Technology 2016 (ICTA 2016) and a section chair of the 4th International Conference on Information System Design and Intelligent Applications (INDIA 2017).

Internet of Everything and Big Data

Internet of Everything and Big Data

There currently is no in-depth book dedicated to the challenge of the Internet of Everything and Big Data technologies in Smart Cities. Humankind today is confronting a critical worldwide portability challenge and the framework that moves cities must keep pace with the innovation. Internet of Everything and Big Data: Major Challenges in Smart Cities reviews the applications, technologies, standards, and other issues related to Smart Cities. The book is dedicated to addressing the major challenges in realizing Smart Cities and sensing platforms in the era of Big Data cities and Internet of Everything. Challenges vary from cost and energy efficiency to availability and service quality. This book examines security issues and challenges, addresses the total information science challenges, covers exploring and creating IoT environment-related sales adaptive systems, and investigates basic and high-level concepts using the latest techniques implemented by researchers and industrial companies. The book is written for analysts, researchers, and specialists who are working on the future generation of the technologies. It will serve as a valuable guide for those in the industry, and students as well.

Artificial Intelligence Trends for Data Analytics Using Machine Learning and Deep Learning Approaches

Artificial Intelligence Trends for Data Analytics Using Machine Learning and Deep Learning Approaches

Author: K. Gayathri (Anna University Chennai) Devi Format: Hardback Release Date: 10/10/2020

Artificial Intelligence (AI), when incorporated with machine learning and deep learning algorithms, has a wide variety of applications today. This book focuses on the implementation of various elementary and advanced approaches in AI that can be used in various domains to solve real-time decision-making problems. The book focuses on concepts and techniques used to run tasks in an automated manner. It discusses computational intelligence in the detection and diagnosis of clinical and biomedical images, covers the automation of a system through machine learning and deep learning approaches, presents data analytics and mining for decision-support applications, and includes case-based reasoning, natural language processing, computer vision, and AI approaches in real-time applications. Academic scientists, researchers, and students in the various domains of computer science engineering, electronics and communication engineering, and information technology, as well as industrial engineers, biomedical engineers, and management, will find this book useful. By the end of this book, you will understand the fundamentals of AI. Various case studies will develop your adaptive thinking to solve real-time AI problems. Features Includes AI-based decision-making approaches Discusses computational intelligence in the detection and diagnosis of clinical and biomedical images Covers automation of systems through machine learning and deep learning approaches and its implications to the real world Presents data analytics and mining for decision-support applications Offers case-based reasoning