This book constitutes the refereed proceedings of the 4th International Conference on Simulation, Modeling, and Programming for Autonomous Robots, SIMPAR 2014, held in Bergamo, Italy, in October 2014.;The 49 revised f...
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ISBN:
(数字)9783319119007
ISBN:
(纸本)9783319118994
This book constitutes the refereed proceedings of the 4th International Conference on Simulation, Modeling, and Programming for Autonomous Robots, SIMPAR 2014, held in Bergamo, Italy, in October 2014.;The 49 revised full papers presented were carefully reviewed and selected from 62 submissions. The papers are organized in topical sections on simulation, modeling, programming, architectures, methods and tools, and systems and applications.
The two volume set LNCS 5506 and LNCS 5507 constitutes the thoroughly refereed post-conference proceedings of the 15th International Conference on Neural Information Processing, ICONIP 2008, held in Auckland, New Zeal...
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ISBN:
(数字)9783642024900
ISBN:
(纸本)9783642024894
The two volume set LNCS 5506 and LNCS 5507 constitutes the thoroughly refereed post-conference proceedings of the 15th International Conference on Neural Information Processing, ICONIP 2008, held in Auckland, New Zealand, in November 2008. The 260 revised full papers presented were carefully reviewed and selected from numerous ordinary paper submissions and 15 special organized sessions. 116 papers are published in the first volume and 112 in the second volume. The contributions deal with topics in the areas of data mining methods for cybersecurity, computational models and their applications to machine learning and pattern recognition, lifelong incremental learning for intelligent systems, application of intelligent methods in ecological informatics, pattern recognition from real-world information by svm and other sophisticated techniques, dynamics of neural networks, recent advances in brain-inspired technologies for robotics, neural information processing in cooperative multi-robot systems.
The two volume set LNCS 5506 and LNCS 5507 constitutes the thoroughly refereed post-conference proceedings of the 15th International Conference on Neural Information Processing, ICONIP 2008, held in Auckland, New Zeal...
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ISBN:
(数字)9783642030406
ISBN:
(纸本)9783642030390
The two volume set LNCS 5506 and LNCS 5507 constitutes the thoroughly refereed post-conference proceedings of the 15th International Conference on Neural Information Processing, ICONIP 2008, held in Auckland, New Zealand, in November 2008. The 260 revised full papers presented were carefully reviewed and selected from numerous ordinary paper submissions and 15 special organized sessions. 116 papers are published in the first volume and 112 in the second volume. The contributions deal with topics in the areas of data mining methods for cybersecurity, computational models and their applications to machine learning and pattern recognition, lifelong incremental learning for intelligent systems, application of intelligent methods in ecological informatics, pattern recognition from real-world information by svm and other sophisticated techniques, dynamics of neural networks, recent advances in brain-inspired technologies for robotics, neural information processing in cooperative multi-robot systems.
The Metaverse presents an emerging creative expression and collaboration frontier where generative artificial intelligence (GenAI) can play a pivotal role with its ability to generate multimodal content from simple pr...
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The Metaverse presents an emerging creative expression and collaboration frontier where generative artificial intelligence (GenAI) can play a pivotal role with its ability to generate multimodal content from simple prompts. These prompts allow the metaverse to interact with GenAI, where context information, instructions, input data, or even output indications constituting the prompt can come from within the metaverse. However, their integration poses challenges regarding interoperability, lack of standards, scalability, and maintaining a high-quality user experience. This paper explores how GenAI can productively assist in enhancing creativity within the contexts of the Metaverse and unlock new opportunities. We provide a technical, in-depth overview of the different generative models for image, video, audio, and 3D content within the Metaverse environments. We also explore the bottlenecks, opportunities, and innovative applications of GenAI from the perspectives of end users, developers, service providers, and AI researchers. This survey commences by highlighting the potential of GenAI for enhancing the Metaverse experience through dynamic content generation to populate massive virtual worlds. Subsequently, we shed light on the ongoing research practices and trends in multimodal content generation, enhancing realism and creativity and alleviating bottlenecks related to standardization, computational cost, privacy, and safety. Lastly, we share insights into promising research directions toward the integration of GenAI with the Metaverse for creative enhancement, improved immersion, and innovative interactive applications.
This book provides several efficient Kalman filters (linear or nonlinear) under information theoretic criteria. They achieve excellent performance in complicated non-Gaussian noises with low computation complexity and...
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ISBN:
(数字)9783031337642
ISBN:
(纸本)9783031337635;9783031337666
This book provides several efficient Kalman filters (linear or nonlinear) under information theoretic criteria. They achieve excellent performance in complicated non-Gaussian noises with low computation complexity and have great practical application potential. The book combines all these perspectives and results in a single resource for students and practitioners in relevant application fields. Each chapter starts with a brief review of fundamentals, presents the material focused on the most important properties and evaluates comparatively the models discussing free parameters and their effect on the results. Proofs are provided at the end of each chapter. The book is geared to senior undergraduates with a basic understanding of linear algebra, signal processing and statistics, as well as graduate students or practitioners with experience in Kalman filtering.
The ability of a robot to build a persistent, accurate, and actionable model of its surroundings through sensor data in a timely manner is crucial for autonomous operation. While representing the world as a point clou...
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The ability of a robot to build a persistent, accurate, and actionable model of its surroundings through sensor data in a timely manner is crucial for autonomous operation. While representing the world as a point cloud might be sufficient for localization, denser scene representations are required for obstacle avoidance. On the other hand, higher-level semantic information is often crucial for breaking down the necessary steps to autonomously complete a complex task, such as cooking. So the looming question is, What is a suitable scene representation for the robotic task at hand? This survey provides a comprehensive review of key approaches and frameworks driving progress in the field of robotic spatial perception, with a particular focus on the historical evolution and current trends in representation. By categorizing scene modeling techniques into three main types—metric, metric–semantic, and metric–semantic–topological—we discuss how spatial perception frameworks are transitioning from building purely geometric models of the world to more advanced data structures incorporating higher-level concepts, such as the notion of object instances and places. Special emphasis is placed on approaches for real-time simultaneous localization and mapping, their integration with deep learning for enhanced robustness and scene understanding, and their ability to handle scene dynamicity as some of the hottest topics of interest driving robotics research today. We conclude with a discussion of ongoing challenges and future research directions in the quest to develop robust and scalable spatial perception systems suitable for long-term autonomy.
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