Attention in Cognitive Systems : Theories and Systems from an Interdisciplinary Viewpoint ; 4th International Workshop on Attention in Cognitive Systems, WAPCV 2007 Hyderabad, India, January 8, 2007 Revised Selected Papers
The embodied nature of sensory-motor intelligence requires a continuous and focused interplay between the control of motor activities and the interpretation of feedback from perceptual modalities. Decision making about the selection of information from the incoming sensory stream – in tune with contextual processing on a current task and an agent’s global objectives – becomes a further challenging issue in attentional control. Attention must operate at interfaces between bottom-up driven world int- pretation and top-down driven information selection, thus acting at the core of arti?cial cognitive systems. These insights have already induced changes in AI-related disciplines, such as the design of behavior-based robot control and the computational modeling of animats. Today, the development of enabling technologiessuch as autonomous robotic systems,miniaturizedmobile–evenwearable–sensors,andambientintelligence systems involves the real-time analysis of enormous quantities of data. These data have to be processed in an intelligent way to provide “on time delivery” of the required relevant information. Knowledge has to be applied about what needs to be attended to, and when, and what to do in a meaningful sequence, in correspondence with visual feedback.
Attention and Performance in Computational Vision ; 2nd International Workshop, WAPCV 2004, Prague, Czech Republic, May 15, 2004, Revised Selected Papers
This book constitutes the thoroughly refereed post-proceedings of the Second International Workshop on Attention and Performance in Computational Vision, WAPCV 2004, held in Prague, Czech Republic in May 2004. The goal of this workshop was to provide an interdisciplinary forum tocommunicatecomputationalmodelsofvisualattentionfromvariousviewpoints,such as from computer vision, psychology, robotics and neuroscience. The motivation for - terdisciplinarity was communication and inspiration beyond the individual community, to focus discussion on computational modelling, to outline relevant objectives for p- formance comparison, to explore promising application domains, and to discuss these with reference to all related aspects of cognitive vision.
Assistive technologies, robotics, and automated machines in the health domain
The field of healthcare is constantly evolving and advancing with new technologies and innovations. Among these, assistive technologies, robotics, and automated machines are rapidly gaining ground as powerful tools to improve the quality of care and enhance patient outcomes. From wearable devices that monitor vital signs to surgical robots that assist in complex procedures, these technologies have the potential to revolutionize the way we deliver healthcare. The development and the integration of assistive technologies, care robots, and automated machines are strategic both as single components, when paired together, and when interconnected in the health domain.This reprint explores the latest developments in assistive technologies, robotics, and automated machines in the health domain, providing a comprehensive overview of their applications and potential impact. The reprint is for the benefit of healthcare professionals, researchers, engineers, and students interested in these rapidly evolving fields.
Artificial neural networks with Java : Tools for Building Neural Network Applications
Covers the internals of front and back propagation and helps you understand the main principles of neural network processing. You also will learn how to prepare the data to be used in neural network development and you will be able to suggest various techniques of data preparation for many unconventional tasks. You will learn: Use Java for the development of neural network applications / Prepare data for many different tasks / Carry out some unusual neural network processing / Use a neural network to process non-continuous functions / Develop a program that recognizes handwritten digits
Artificial neural networks in Pattern Recognition ; 9th IAPR TC3 Workshop, ANNPR 2020, Winterthur, Switzerland, September 2–4, 2020, Proceedings
This book constitutes the refereed proceedings of the 9th IAPR TC3 International Workshop on Artificial Neural Networks in Pattern Recognition, ANNPR 2020, held in Winterthur, Switzerland, in September 2020. The conference was held virtually due to the COVID-19 pandemic. The 22 revised full papers presented were carefully reviewed and selected from 34 submissions. The papers present and discuss the latest research in all areas of neural network-and machine learning-based pattern recognition. They are organized in two sections: learning algorithms and architectures, and applications.
Artificial neural networks in Pattern Recognition ; 3d IAPR Workshop, ANNPR 2008 Paris, France, July 2-4, 2008 Proceedings
Constitutes the refereed proceedings of the Third TC3 IAPR Workshop on Artificial Neural Networks in Pattern Recognition, ANNPR 2008, held in Paris, France, in July 2008.
Artificial neural networks : Recent advances, new perspectives and applications
This book explores the potential of ANNs for applications in different fields. Itincludes eight chapters that discuss deep learning, ANN tools, and other cutting-edgetechnologies. It also suggests avenues for further research into ANN techniques formedical imaging to detect breast tumors, classification of COVID-19 surveillancedatasets, health management, estimation of materials processing parameters, solarenergy management, and control of a petrochemical unit.
Artificial neural networks : Formal Models and Their Applications – ICANN 2005 ; 15th International Conference, Warsaw, Poland, September 11-15, 2005, Proceedings, Part II
The second volume contains 162 contributions related to Formal Models and their Applications and deals with new neural network models, supervised learning algorithms, ensemble-based learning, unsupervised learning, recurent neural networks, reinforcement learning, bayesian approaches to learning, learning theory, artificial neural networks for system modeling, decision making, optimalization and control, knowledge extraction from neural networks, temporal data analysis, prediction and forecasting, support vector machines and kernel-based methods, soft computing methods for data representation, analysis and processing, data fusion for industrial, medical and environmental applications, non-linear predictive models for speech processing, intelligent multimedia and semantics, applications to natural language processing, various applications, computational intelligence in games, and issues in hardware implementation.
Artificial neural networks : Biological Inspirations – ICANN 2005 ; 15th International Conference, Warsaw, Poland, September 11-15, 2005, Proceedings, Part I
The two volume set LNCS 3696 and LNCS 3697 constitutes the refereed proceedings of the 15th International Conference on Artificial Neural Networks, ICANN 2005, held in Warsaw, Poland in September 2005. The over 600 papers submitted to ICANN 2005 were thoroughly reviewed and carefully selected for presentation. The first volume includes 106 contributions related to Biological Inspirations; topics addressed are modeling the brain and cognitive functions, development of cognitive powers in embodied systems spiking neural networks, associative memory models, models of biological functions, projects in the area of neuroIT, evolutionary and other biological inspirations, self-organizing maps and their applications, computer vision, face recognition and detection, sound and speech recognition, bioinformatics, biomedical applications, and information- theoretic concepts in biomedical data analysis.
Artificial neural networks - ICANN 2008 ; 18th International Conference, Prague, Czech Republic, September 3-6, 2008, Proceedings, Part II
This two volume set LNCS 5163 and LNCS 5164 constitutes the refereed proceedings of the 18th International Conference on Artificial Neural Networks, ICANN 2008, held in Prague Czech Republic, in September 2008.
Artificial neural networks - ICANN 2008 ; 18th International Conference, Prague, Czech Republic, September 3-6, 2008, Proceedings, Part I
This two volume set LNCS 5163 and LNCS 5164 constitutes the refereed proceedings of the 18th International Conference on Artificial Neural Networks, ICANN 2008, held in Prague Czech Republic, in September 2008.
Artificial neural networks - ICANN 2006 ; Vol.4132 : 16th International Conference, Athens, Greece, September 10-14, 2006, Proceedings, Part II
This book includes the proceedings of the International Conference on Artificial Neural Networks (ICANN 2006) held on September 10-14, 2006 in Athens, Greece, with tutorials being presented on September 10, the main conference taking place during September 11-13 and accompanying workshops on perception, cognition and interaction held on September 14, 2006. The ICANN conference is organized annually by the European Neural Network Society in cooperation with the International Neural Network Society, the Japanese Neural Network Society and the IEEE Computational Intelligence Society. It is the premier European event covering all topics concerned with neural networks and related areas.
Artificial neural networks - ICANN 2006 ; Vol.4131 : 16th International Conference, Athens, Greece, September 10-14, 2006, Proceedings, Part I
This book includes the proceedings of the International Conference on Artificial Neural Networks (ICANN 2006) held on September 10-14, 2006 in Athens, Greece, with tutorials being presented on September 10, the main conference taking place during September 11-13 and accompanying workshops on perception, cognition and interaction held on September 14, 2006. The ICANN conference is organized annually by the European Neural Network Society in cooperation with the International Neural Network Society, the Japanese Neural Network Society and the IEEE Computational Intelligence Society. It is the premier European event covering all topics concerned with neural networks and related areas.
Artificial neural network-based optimized design of reinforced concrete structures
Introduces AI-based Lagrange optimization techniques that can enable more rational engineering decisions for concrete structures while conforming to codes of practice. It shows how objective functions including cost, CO2 emissions, and structural weight of concrete structures are optimized either separately or simultaneously while satisfying constraining design conditions using an ANN-based Lagrange algorithm. Any design target can be adopted as an objective function. Many optimized design examples are verified by both conventional structural calculations and big datasets. Uniquely applies the new powerful tools of AI to concrete structural design and optimization Multi-objective functions of concrete structures optimized either separately or simultaneously Design requirements imposed by codes are automatically satisfied by constraining conditions Heavily illustrated in color with practical design examples
Artificial life models in software
Artificial Life Models in Software presents software tools, environments and realities dealing with creation, imitation and analysis of artefactual, virtual and living forms, written by those who personally design and produce software, hardware and art installations in artificial life, simulated complex systems and virtual worlds. This timely volume offers a nearly exhaustive overview and original analysis of major non-profit artificial life software packages. The carefully selected topics include: · simulation of real and imaginary life forms and their evolution · self-organization · emergent behaviours · swarm intelligence · evolutionary robotics · agent-based simulations · adaptive, complex and biologically inspired ecosystems · creative computer art There has long been a need within the academic and research community for an informal introduction and guidance to modern software tools for modelling and simulation of life-like phenomena – Artificial Life Models in Software fills this gap and provides invaluable information to both professional and amateur readers, offering detailed reviews of contemporary software for artificial life.
Artificial Intelligent Techniques for Wireless Communication and Networking
Wireless communication and networking based on AI concepts and techniques are explored in this book, specifically focusing on the current research in the field by highlighting empirical results along with theoretical concepts. The possibility of applying AI mechanisms towards security aspects in the communication domain is elaborated; also explored is the application side of integrated technologies that enhance AI-based innovations, insights, intelligent predictions, cost optimization, inventory management, identification processes, classification mechanisms, cooperative spectrum sensing techniques, ad-hoc network architecture, and protocol and simulation-based environments.
Artificial intelligence-based Internet of things systems
Discusses the evolution of future generation technologies through Internet of Things (IoT) in the scope of Artificial Intelligence (AI). The main focus of this volume is to bring all the related technologies in a single platform, so that undergraduate and postgraduate students, researchers, academicians, and industry people can easily understand the AI algorithms, machine learning algorithms, and learning analytics in IoT-enabled technologies. This book uses data and network engineering and intelligent decision support system-by-design principles to design a reliable AI-enabled IoT ecosystem and to implement cyber-physical pervasive infrastructure solutions. This book brings together some of the top IoT-enabled AI experts throughout the world who contribute their knowledge regarding different IoT-based technology aspects. Addresses the complete functional framework workflow in AI-enabled IoT ecosystem; Presents intelligent object identification and object discovery through the IoT ecosystem and its implications to the real world ;Explores security and privacy issues and trustworthy machine learning related to data-intensive technologies in AI-based IoT ecosystems.
Artificial Intelligence. IJCAI 2019 International Workshops ; Macao, China, August 10–12, 2019, Revised Selected Best Papers
This book presents selected papers of 12 Workshops held in conjunction with the 28th International Joint Conference on Artificial Intelligence, IJCAI 2019, in Macao, China, in August 2019.
Artificial Intelligence with Python
Introduces readers to various topics and examples of programming in Python, as well as key concepts in artificial intelligence. Python programming skills will be imparted as we go along. Concepts and code snippets will be covered in a step-by-step manner, to guide and instill confidence in beginners. Complex subjects in deep learning and machine learning will be broken down into easy-to-digest content and examples. Artificial intelligence implementations will also be shared, allowing beginners to generate their own artificial intelligence algorithms for reinforcement learning, style transfer, chatbots, speech, and natural language processing.
Artificial intelligence techniques in hydrology and water resources management
The sustainable management of water cycles is crucial in the context of climate change and global warming. It involves managing global, regional, and local water cycles, as well as urban, agricultural, and industrial water cycles, to conserve water resources and their relationships with energy, food, microclimates, biodiversity, ecosystem functioning, and anthropogenic activities. Hydrological modeling is indispensable for achieving this goal, as it is essential for water resources management and the mitigation of natural disasters. In recent decades, the application of artificial intelligence (AI) techniques in hydrology and water resources management has led to notable advances. In the face of hydro-geo-meteorological uncertainty, AI approaches have proven to be powerful tools for accurately modeling complex, nonlinear hydrological processes and effectively utilizing various digital and imaging data sources, such as ground gauges, remote sensing tools, and in situ Internet of Things (IoT) devices.



















