Current Approaches In Applied Artificial Intelligence
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Current Approaches In Applied Artificial Intelligence
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Author : Moonis Ali
language : en
Publisher: Springer
Release Date : 2015-04-30
Current Approaches In Applied Artificial Intelligence written by Moonis Ali and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-04-30 with Computers categories.
This book constitutes the refereed conference proceedings of the 28th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2015, held in Seoul, South Korea, in June 2015. The 73 revised full papers presented were carefully reviewed and selected from 105 submissions. The papers cover a wide range of topics in applied artificial intelligence including reasoning, robotics, cognitive modeling, machine learning, pattern recognition, optimization, text mining, social network analysis, and evolutionary algorithms. They are organized in the following topical sections: theoretical AI, knowledge-based systems, optimization, Web and social networks, machine learning, classification, unsupervised learning, vision, image and text processing, and intelligent systems applications.
Current Approaches In Applied Artificial Intelligence
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Author : Moonis Ali
language : en
Publisher:
Release Date : 2015
Current Approaches In Applied Artificial Intelligence written by Moonis Ali and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with categories.
This book constitutes the refereed conference proceedings of the 28th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2015, held in Seoul, South Korea, in June 2015. The 73 revised full papers presented were carefully reviewed and selected from 105 submissions. The papers cover a wide range of topics in applied artificial intelligence including reasoning, robotics, cognitive modeling, machine learning, pattern recognition, optimization, text mining, social network analysis, and evolutionary algorithms. They are organized in the following topical sections: theoretical AI, knowledge-based systems, optimization, Web and social networks, machine learning, classification, unsupervised learning, vision, image and text processing, and intelligent systems applications.
Explainable Ai With Python
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Author : Leonida Gianfagna
language : en
Publisher: Springer Nature
Release Date : 2021-04-28
Explainable Ai With Python written by Leonida Gianfagna and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-04-28 with Computers categories.
This book provides a full presentation of the current concepts and available techniques to make “machine learning” systems more explainable. The approaches presented can be applied to almost all the current “machine learning” models: linear and logistic regression, deep learning neural networks, natural language processing and image recognition, among the others. Progress in Machine Learning is increasing the use of artificial agents to perform critical tasks previously handled by humans (healthcare, legal and finance, among others). While the principles that guide the design of these agents are understood, most of the current deep-learning models are "opaque" to human understanding. Explainable AI with Python fills the current gap in literature on this emerging topic by taking both a theoretical and a practical perspective, making the reader quickly capable of working with tools and code for Explainable AI. Beginning with examples of what Explainable AI (XAI) is and why it is needed in the field, the book details different approaches to XAI depending on specific context and need. Hands-on work on interpretable models with specific examples leveraging Python are then presented, showing how intrinsic interpretable models can be interpreted and how to produce “human understandable” explanations. Model-agnostic methods for XAI are shown to produce explanations without relying on ML models internals that are “opaque.” Using examples from Computer Vision, the authors then look at explainable models for Deep Learning and prospective methods for the future. Taking a practical perspective, the authors demonstrate how to effectively use ML and XAI in science. The final chapter explains Adversarial Machine Learning and how to do XAI with adversarial examples.
Applied Artificial Intelligence
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Author : Bernhard G. Humm
language : en
Publisher:
Release Date : 2016
Applied Artificial Intelligence written by Bernhard G. Humm and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016 with Artificial intelligence categories.
Modern AI applications are not built from scratch but by integrating off-the-shelf components: libraries, frameworks, and services. This insightful resource focuses on engineering user friendly, high-performance, and maintainable AI applications. --
Recent Trends In Applied Artificial Intelligence
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Author : Moonis Ali
language : en
Publisher: Springer
Release Date : 2013-05-20
Recent Trends In Applied Artificial Intelligence written by Moonis Ali and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-05-20 with Computers categories.
This volume constitutes the thoroughly refereed conference proceedings of the 26th International Conference on Industrial Engineering and Other Applications of Applied Intelligence Systems, IEA/AIE 2013, held in Amsterdam, The Netherlands, in June 2013. The total of 71 papers selected for the proceedings were carefully reviewed and selected from 185 submissions. The papers focus on the following topics: auctions and negotiation, cognitive modeling, crowd behavior modeling, distributed systems and networks, evolutionary algorithms, knowledge representation and reasoning, pattern recognition, planning, problem solving, robotics, text mining, advances in recommender systems, business process intelligence, decision support for safety-related systems, innovations in intelligent computation and applications, intelligent image and signal processing, and machine learning methods applied to manufacturing processes and production systems.
Advances In Applied Artificial Intelligence
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Author : Fulcher, John
language : en
Publisher: IGI Global
Release Date : 2006-03-31
Advances In Applied Artificial Intelligence written by Fulcher, John and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-03-31 with Computers categories.
"This book explores artificial intelligence finding it cannot simply display the high-level behaviours of an expert but must exhibit some of the low level behaviours common to human existence"--Provided by publisher.
Innovations In Applied Artificial Intelligence
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Author : Floriana Esposito
language : en
Publisher: Springer Science & Business Media
Release Date : 2005-06-16
Innovations In Applied Artificial Intelligence written by Floriana Esposito and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-06-16 with Computers categories.
“Intelligent systems are those which produce intelligent o?springs.” AI researchers have been focusing on developing and employing strong methods that are capable of solving complex real-life problems. The 18th International Conference on Industrial & Engineering Applications of Arti?cial Intelligence & Expert Systems (IEA/AIE 2005) held in Bari, Italy presented such work performed by many scientists worldwide. The Program Committee selected long papers from contributions presenting more complete work and posters from those reporting ongoing research. The Committee enforced the rule that only original and unpublished work could be considered for inclusion in these proceedings. The Program Committee selected 116 contributions from the 271 subm- ted papers which cover the following topics: arti?cial systems, search engines, intelligent interfaces, knowledge discovery, knowledge-based technologies, na- ral language processing, machine learning applications, reasoning technologies, uncertainty management, applied data mining, and technologies for knowledge management. The contributions oriented to the technological aspects of AI and the quality of the papers are witness to a research activity clearly aimed at consolidating the theoretical results that have already been achieved. The c- ference program also included two invited lectures, by Katharina Morik and Roberto Pieraccini. Manypeoplecontributedindi?erentwaystothesuccessoftheconferenceand to this volume. The authors who continue to show their enthusiastic interest in applied intelligence research are a very important part of our success. We highly appreciate the contribution of the members of the Program Committee, as well as others who reviewed all the submitted papers with e?ciency and dedication.
Artificial Intelligence And Machine Learning Methods In Covid 19 And Related Health Diseases
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Author : Victor Chang
language : en
Publisher: Springer Nature
Release Date : 2022-06-28
Artificial Intelligence And Machine Learning Methods In Covid 19 And Related Health Diseases written by Victor Chang and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-28 with Technology & Engineering categories.
This Springer book provides a perfect platform to submit chapters that discuss the prospective developments and innovative ideas in artificial intelligence and machine learning techniques in the diagnosis of COVID-19. COVID-19 is a huge challenge to humanity and the medical sciences. So far as of today, we have been unable to find a medical solution (Vaccine). However, globally, we are still managing the use of technology for our work, communications, analytics, and predictions with the use of advancement in data science, communication technologies (5G & Internet), and AI. Therefore, we might be able to continue and live safely with the use of research in advancements in data science, AI, machine learning, mobile apps, etc., until we can find a medical solution such as a vaccine. We have selected eleven chapters after the vigorous review process. Each chapter has demonstrated the research contributions and research novelty. Each group of authors must fulfill strict requirements.
Applied Artificial Intelligence
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Author : Bernhard G Humm
language : en
Publisher:
Release Date : 2020-04-09
Applied Artificial Intelligence written by Bernhard G Humm and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-04-09 with categories.
Why yet another book on Artificial Intelligence? It is true that hundreds of publications on Artificial Intelligence (AI) have been published within the last decades - scientific papers and text books. Most of them focus on the theory behind AI solutions: logic, reasoning, statistical foundations, etc. However, little can be found on engineering AI applications.Modern, complex IT applications are not built from scratch but by integrating off-the-shelf components: libraries, frameworks, and services. The same applies, of course, for AI applications. Over the last decades, numerous off-the-shelf components for AI base functionality such as logic, reasoning, and statistics have been implemented - commercial and open source. Integrating such components into user friendly, high-performance, and maintainable AI applications requires specific engineering skills. "Applied Artificial Intelligence - An Engingeering Approach" focuses on those skills.
Modern Approaches In Machine Learning And Cognitive Science A Walkthrough
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Author : Vinit Kumar Gunjan
language : en
Publisher: Springer Nature
Release Date : 2024-01-13
Modern Approaches In Machine Learning And Cognitive Science A Walkthrough written by Vinit Kumar Gunjan and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-01-13 with Technology & Engineering categories.
This book provides a systematic and comprehensive overview of cognitive intelligence and AI-enabled IoT ecosystem and machine learning, capable of recognizing the object pattern in complex and large data sets. A remarkable success has been experienced in the last decade by emulating the brain–computer interface. It presents the applied cognitive science methods and AI-enabled technologies that have played a vital role at the core of practical solutions for a wide scope of tasks between handheld apps and industrial process control, autonomous vehicles, IoT, intelligent learning environment, game theory, human computer interaction, environmental policies, life sciences, playing computer games, computational theory, and engineering development. The book contains contents highlighting artificial neural networks that are analogous to the networks of neurons that comprise the brain and have given computers the ability to distinguish an image of a cat from one of a coconut, to spot pedestrians with enough accuracy to direct a self-driving car, and to recognize and respond to the spoken word. The chapters in this book focus on audiences interested in artificial intelligence, machine learning, fuzzy, cognitive and neurofuzzy-inspired computational systems, their theories, mechanisms, and architecture, which underline human and animal behavior, and their application to conscious and intelligent systems. In the current version, it focuses on the successful implementation and step-by-step execution and explanation of practical applications of the domain. It also offers a wide range of inspiring and interesting cutting-edge contributions on applications of machine learning, artificial intelligence, and cognitive science such as healthcare products, AI-enabled IoT, gaming, medical, and engineering. Overall, this book provides valuable information on effective, cutting-edge techniques, and approaches for students, researchers, practitioners, and academics in the field of machine learning and cognitive science. Furthermore, the purpose of this book is to address the interests of a broad spectrum of practitioners, students, and researchers, who are interested in applying machine learning and cognitive science methods in their respective domains.