Modern Deep Learning Design and Application Development : Versatile Tools to Solve Deep Learning Problems
Learn how to harness modern deep-learning methods in many contexts. Packed with intuitive theory, practical implementation methods, and deep-learning case studies, this book reveals how to acquire the tools you need to design and implement like a deep-learning architect. It covers tools deep learning engineers can use in a wide range of fields, from biology to computer vision to business. With nine in-depth case studies, this book will ground you in creative, real-world deep learning thinking. You will: Improve the performance of deep learning models by using pre-trained models, extracting rich features, and automating optimization. Compress deep learning models while maintaining performance. Reframe a wide variety of difficult problems and design effective deep learning solutions to solve them. Use the Keras framework, with some help from libraries like HyperOpt, TensorFlow, and PyTorch, to implement a wide variety of deep learning approaches.
Models, Methods and Tools for Product Service Design : The Manutelligence Project
This book summarizes research being pursued within the Manutelligence project, the goal of which is to help enterprises develop smart, social and flexible products with high value added services. Manutelligence has improved Product and Service Design by developing suitable models and methods, and connecting them through a modular, collaborative and secure ICT Platform. The use of real data collected in real time by Internet of Things (IoT) technologies underpins the design of product-service systems and makes it possible to monitor them throughout their life cycle. Available data allows costs and sustainability issues to be more accurately measured and simulated in the form of Life Cycle Cost (LCC) and Life Cycle Assessment (LCA). Analysing data from IoT systems and sharing LCC and LCA information via the ICT Platform can help to accelerate the design of product-service systems, reduce costs and better understand customer needs. Industrial partners involved in Manutelligence provide a clear overview of the project's outcomes, and demonstrate how its technological solutions can be used to improve the design of product-service systems and the management of product-service life cycles.
Modelling and Development of Intelligent Systems ; 6th International Conference, MDIS 2019, Sibiu, Romania, October 3–5, 2019, Revised Selected Papers
This volume constitutes the refereed proceedings of the 6th International Conference on Modelling and Development of Intelligent Systems, MDIS 2019, held in Sibiu, Romania, in October 2019. The 13 revised full papers presented in the volume were carefully reviewed and selected from 31 submissions. The papers are organized in topical sections on adaptive systems; conceptual modelling; data mining; intelligent systems for decision support; machine learning.
Modelling and Control of Mini-Flying Machines
Modelling and Control of Mini-Flying Machines is an exposition of models developed for various types of mini-aircraft. Modelling and Control of Mini-Flying Machines provides valuable insights to the application of real-time nonlinear techniques in an always challenging area.
Modeling, Simulation and Optimization of Complex Processes HPSC 2018 ; Proceedings of the 7th International Conference on High Performance Scientific Computing, Hanoi, Vietnam, March 19-23, 2018
The contributions cover a broad, interdisciplinary spectrum of scientific computing and showcase recent advances in theory, methods, and practical applications. Subjects covered include numerical simulation, methods for optimization and control, machine learning, parallel computing and software development, as well as the applications of scientific computing in mechanical engineering, airspace engineering, environmental physics, decision making, hydrogeology, material science and electric circuits.
Modeling Decisions for Artificial Intelligence ; Vol.3885 ; 3rd International Conference, MDAI 2006, Tarragona, Spain, April 3-5, 2006, Proceedings
This book constitutes the refereed proceedings of the Third International Conference on Modeling Decisions for Artificial Intelligence, MDAI 2006, held in Tarragona, Spain, in April 2006.
Modeling Decisions for Artificial Intelligence ; 4th International Conference, MDAI 2007, Kitakyushu, Japan, August 16-18, 2007, Proceedings
Decision modeling is a key area in the developing field of AI, and this timely work connects researchers and professionals with the very latest research. It constitutes the refereed proceedings of the 4th International Conference on Modeling Decisions for Artificial Intelligence, held in Kitakyushu, Japan, in August 2007.
Modeling Communication with Robots and Virtual Humans ; Second ZiF Research Group International Workshop on Embodied Communication in Humans and Machines, Bielefeld, Germany, April 5-8, 2006, Revised Selected Papers
The 17 articles in this state-of-the-art survey address artificial intelligence research on communicative agents and also provide an interdisciplinary perspective from linguistics, behavioral research, theoretical biology, philosophy, communication psychology, and computational neuroscience. The topics include studies on human multimodal communication; the modeling of feedback signals, facial expression, eye contact, and deception; the recognition and comprehension of hand gestures and head movements; communication interfaces for humanoid robots; the evolution of cognition and language; emotion and social appraisal in nonverbal communication; dialogue models and methodologies; theory of mind and intentionality; complex systems, dynamic field theory, and connectionist modeling.
Model-Based Testing of Reactive Systems : Advanced Lectures
This book is based on a seminar held in Dagstuhl Castle, Germany, in January 2004. It presents 19 carefully reviewed and revised lectures given at the seminar in a well-balanced way ensuring competent complementary coverage of all relevant aspects. An appendix provides a glossary for model-based testing and basics on finite state machines and on labelled transition systems. The lectures are presented in topical sections on testing of finite state machines, testing of labelled transition systems, model-based test case generation, tools and case studies, standardized test notation and execution architectures, and beyond testing.
Mobile health technologies for ambient assisted living and healthcare
The use of telemedicine and mobile devices is growing, and sensors might aid in creating creative solutions. Developing these solutions is crucial for monitoring senior citizens, lifestyles, and medical procedures. The development of assistive technology for various users to follow sports and other activities is strongly tied to this study area. Data protection is crucial, and the development of these solutions for medical uses should be verified. The security and privacy of the information may be tied to other recognized research projects for their acceptability. ICT research has considerably improved quality of life and has fully assimilated all citizens into society through medical rehabilitation and assistive technology. The technologies and research fields that influence medical informatics include databases, networking, graphical user interfaces, data mining, machine learning, intelligent decision support systems, and specialized programming languages.
Mobile Edge Computing
It offers comprehensive, self-contained knowledge on Mobile Edge Computing (MEC), which is a very promising technology for achieving intelligence in the next-generation wireless communications and computing networks. The book starts with the basic concepts, key techniques and network architectures of MEC. Then, we present the wide applications of MEC, including edge caching, 6G networks, Internet of Vehicles, and UAVs. In the last part, we present new opportunities when MEC meets blockchain, Artificial Intelligence, and distributed machine learning (e.g., federated learning). We also identify the emerging applications of MEC in pandemic, industrial Internet of Things and disaster management.
Mobile computing, applications, and services ; 11th EAI International Conference, MobiCASE 2020, Shanghai, China, September 12, 2020, Proceedings
This book constitutes the thoroughly refereed post-conference proceedings of the 11th International Conference on Mobile Computing, Applications, and Services, MobiCASE 2020, held in Shanghai, China, in September 2020. The conference was held virtually due to the COVID-19 pandemic. The 15 full papers were carefully reviewed and selected from 49 submissions. The papers are organized in topical sections on mobile application and framework; mobile application with data analysis; and AI application.
Mobile and Wireless Communications with Practical Use-Case Scenarios
While wireless technologies had a spectacular evolution over the past years, the present trend is to adopt a global heterogeneous network of shared standards that enables the provisioning of Quality of Service and Quality of Experience to the end-user. To this end, enabling technologies like Machine Learning, Internet of Things, Digital Twins, are seen as promising solutions for next generation networks that will enable an intelligent adaptive interconnected environment with support for prediction and decision making so that the heterogeneous applications and users requirements can be highly satisfied. The aim of this textbook is to provide the readers with a comprehensive technical foundation of the mobile communication systems and wireless network design, operations and applications of various radio access technologies. Additionally, it also introduces the reader to the latest advancements in technologies in terms of Internet of Things ecosystem, Machine Learning and Digital Twins for IoT-enabled intelligent environments. Furthermore, this textbook also includes practical use-case scenarios using Altair WinProp Software as well as Phyton, TensorFlow and Jupiter as support for practice-based laboratory sessions"
Mind conversation = التنبؤ بالحروف العربية من خلال الإشارات الدماغية
Throughout history, humans have long dreamed of understanding what goes on inside the human mind—what people are thinking or feeling. It seemed like something from a far-off future or a magical realm. But now, thanks to amazing technology called EEG and BCI, this dream is turning into reality. EEG stands for electroencephalography. It's a way of listening to what the brain is up to by placing small sensors on or near the head. These sensors pick up tiny electrical signals produced by the brain's activity. It's like eavesdropping on the brain's conversations with itself. BCI, or Brain-Computer Interface, is like a bridge between the brain and machines. It lets the brain talk to devices or computers. This means people can control things without using their hands or voices. Our system takes advantage of EEG and BCI to create something helpful, a special mobile app. This app is designed for people who can't move their bodies, like those who are paralyzed. It helps them use their phones to express what they are thinking about.
MICAI 2008 : Advances in Artificial Intelligence ;7th Mexican International Conference on Artificial Intelligence, Atizapán de Zaragoza, Mexico, October 27-31, 2008 Proceedings
The 96 revised full papers presented together with 2 invited lectures were carefully reviewed and selected from 363 submissions. The papers are organized in topical sections on logic and reasoning, knowledge-based systems, knowledge representation and acquisition, ontologies, natural language processing, machine learning, pattern recognition, data mining, neural networks, genetic algorithms, hybrid intelligent systems, computer vision and image processing, robotics, planning and scheduling, uncertainty and probabilistic reasoning, fuzzy logic, intelligent tutoring systems, multi-agent systems and distributed ai, intelligent organizations, bioinformatics and medical applications, as well as applications.
MICAI 2007 : Advances in artificial intelligence ; 6th Mexican International Conference on Artificial Intelligence, Aguascalientes, Mexico, November 4-10, 2007, Proceedings
The Mexican International Conference on Artificial Intelligence (MICAI), a yearly international conference series organized by the Mexican Society for Artificial Intelligence (SMIA), is a major international AI forum and the main event in the academic life of the country’s growing AI community.
MICAI 2006 : Advances in Artificial Intelligence ; 5th Mexican International Conference on Artificial Intelligence, Apizaco, Mexico, November 13-17, 2006, Proceedings
This volume contains the papers presented during the oral session of the 5 Mexican International Conference on Artificial Intelligence, held on November 13–17, 2006, at the Technologic Institute of Apizaco, Mexico. The conference received for evaluation 448 submissions by 1207 authors from 42 different countries
MICAI 2005 : Advances in Artificial Intelligence ; 4th Mexican International Conference on Artificial Intelligence, Monterrey, Mexico, November 14-18, 2005, Proceedings
Constitutes the refereed proceedings of the 4th Mexican International Conference on Artificial Intelligence, MICAI 2005, held Mexico, in November 2005. This book is organized in topical sections on knowledge representation and management, logic and constraint programming, uncertainty reasoning, multiagent systems and distributed AI, and others.
Metalearning : Applications to Automated Machine Learning and Data Mining
This book as one of the fastest-growing areas of research in machine learning, metalearning studies principled methods to obtain efficient models and solutions by adapting machine learning and data mining processes. This adaptation usually exploits information from past experience on other tasks and the adaptive processes can involve machine learning approaches. As a related area to metalearning and a hot topic currently, automated machine learning (AutoML) is concerned with automating the machine learning processes. Metalearning and AutoML can help AI learn to control the application of different learning methods and acquire new solutions faster without unnecessary interventions from the user.
Medical Image Computing and Computer-Assisted Intervention – MICCAI 2005 ; 8th International Conference, Palm Springs, CA, USA, October 26-29, 2005, Proceedings, Part I
This paper presents a method for classification of medical images, using machine learning and deformation-based morphometry. A morphological representation of the anatomy of interest is first obtained using highdimensional template warping, from which regions that display strong correlations between morphological measurements and the classification (clinical) variable are extracted using a watershed segmentation, taking into account the regional smoothness of the correlation map which is estimated by a crossvalidation strategy in order to achieve robustness to outliers. A Support Vector Machine-Recursive Feature Elimination (SVM-RFE) technique is then used to rank computed features from the extracted regions, according to their effect on the leave-one-out error bound. Finally, SVM classification is applied using the best set of features, and it is tested using leave-one-out. The results from a group of 61 brain images of female normal controls and schizophrenia patients demonstrate not only high classification accuracy (91.8%) and steep ROC curves, but also exceptional stability with respect to the number of selected features and the SVM kernel size



















