Download or read book Robust Kernel Methods in Context dependent Fusion written by Gyeongyong Heo and published by . This book was released on 2009 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: By adding the regularization terms, not only does CDF-R achieve noise robustness, the main purpose of regularization, but the consequent clusters, which need not be convex, result in better performance than CDF. Although CDF-R is better at classification than CDF, the linear separability does not change. To completely remove the limitation, CDF is transformed to be non-linear, termed kernel-based context-dependent fusion (K-CDF). K-CDF adopts modified kernel methods to remove the restrictions of CDF and remedies some problems in the original kernel methods. K-CDF consists of three main components: dimension reduction, feature space clustering, and fusion. For each component, robust kernel fuzzy principal component analysis (RKF-PCA), kernel-based global fuzzy c-means (KG-FCM), and fuzzy support vector machine for noisy data (FSVM-N) are formulated, and which correspond to the robust variant of kernel PCA, kernel FCM, and fuzzy SVM, respectively. Although the three modifications were originated to address different shortcomings, one common purpose is to reduce the effect of nose, i.e., making the kernel methods noise-robust. By combining the three robust kernel methods, not only does K-CDF overcome the convex cluster assumption and linearly separable restriction, but it achieves noise robustness and better performance than previous methods.
Download or read book Sparse and Robust Kernel Methods written by Andrew Guillermo Peter Naish-Guzman and published by . This book was released on 2008 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Multisensor Data Fusion written by Hassen Fourati and published by CRC Press. This book was released on 2017-12-19 with total page 639 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multisensor Data Fusion: From Algorithms and Architectural Design to Applications covers the contemporary theory and practice of multisensor data fusion, from fundamental concepts to cutting-edge techniques drawn from a broad array of disciplines. Featuring contributions from the world’s leading data fusion researchers and academicians, this authoritative book: Presents state-of-the-art advances in the design of multisensor data fusion algorithms, addressing issues related to the nature, location, and computational ability of the sensors Describes new materials and achievements in optimal fusion and multisensor filters Discusses the advantages and challenges associated with multisensor data fusion, from extended spatial and temporal coverage to imperfection and diversity in sensor technologies Explores the topology, communication structure, computational resources, fusion level, goals, and optimization of multisensor data fusion system architectures Showcases applications of multisensor data fusion in fields such as medicine, transportation's traffic, defense, and navigation Multisensor Data Fusion: From Algorithms and Architectural Design to Applications is a robust collection of modern multisensor data fusion methodologies. The book instills a deeper understanding of the basics of multisensor data fusion as well as a practical knowledge of the problems that can be faced during its execution.
Download or read book New Development in Robot Vision written by Yu Sun and published by Springer. This book was released on 2014-09-26 with total page 209 pages. Available in PDF, EPUB and Kindle. Book excerpt: The field of robotic vision has advanced dramatically recently with the development of new range sensors. Tremendous progress has been made resulting in significant impact on areas such as robotic navigation, scene/environment understanding, and visual learning. This edited book provides a solid and diversified reference source for some of the most recent important advancements in the field of robotic vision. The book starts with articles that describe new techniques to understand scenes from 2D/3D data such as estimation of planar structures, recognition of multiple objects in the scene using different kinds of features as well as their spatial and semantic relationships, generation of 3D object models, approach to recognize partially occluded objects, etc. Novel techniques are introduced to improve 3D perception accuracy with other sensors such as a gyroscope, positioning accuracy with a visual servoing based alignment strategy for microassembly, and increasing object recognition reliability using related manipulation motion models. For autonomous robot navigation, different vision-based localization and tracking strategies and algorithms are discussed. New approaches using probabilistic analysis for robot navigation, online learning of vision-based robot control, and 3D motion estimation via intensity differences from a monocular camera are described. This collection will be beneficial to graduate students, researchers, and professionals working in the area of robotic vision.
Download or read book Kernel Methods and Machine Learning written by S. Y. Kung and published by Cambridge University Press. This book was released on 2014-04-17 with total page 617 pages. Available in PDF, EPUB and Kindle. Book excerpt: Offering a fundamental basis in kernel-based learning theory, this book covers both statistical and algebraic principles. It provides over 30 major theorems for kernel-based supervised and unsupervised learning models. The first of the theorems establishes a condition, arguably necessary and sufficient, for the kernelization of learning models. In addition, several other theorems are devoted to proving mathematical equivalence between seemingly unrelated models. With over 25 closed-form and iterative algorithms, the book provides a step-by-step guide to algorithmic procedures and analysing which factors to consider in tackling a given problem, enabling readers to improve specifically designed learning algorithms, build models for new applications and develop efficient techniques suitable for green machine learning technologies. Numerous real-world examples and over 200 problems, several of which are Matlab-based simulation exercises, make this an essential resource for graduate students and professionals in computer science, electrical and biomedical engineering. Solutions to problems are provided online for instructors.
Download or read book Electrical Electronics Abstracts written by and published by . This book was released on 1997 with total page 1860 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Proceedings of the International Conference of Fluid Power and Mechatronic Control Engineering ICFPMCE 2022 written by Liang Yan and published by Springer Nature. This book was released on 2023-02-10 with total page 415 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is an open access book. Since 1985, held 22 times in different cities all over China, ICFPMCE has now been listed in annual academic activities (non-profit) of the Chinese Society of Theoretical and Applied Mechanics (CSTAM), which has become one of the significant conferences in the field of fluid power and mechatronic control engineering. Under the theme of ‘Green Intelligence, Innovative Development’, ICFPMCE 2022 aims to provide a platform for the participants who have been working in the fields of Fluid mechanics, hydraulic and electrical engineering. In addition to keynote speeches and technical sessions to be hosted by famous experts over the world, the conference will organize a number of mini-symposia with themes of sharing the experiences of applying for the National Natural Science Foundation of China, dialogues between editors-in-chief of the journals and young scholars, experts and entrepreneurs, as well as innovative technology exhibition etc., in order to highlight the significant subjects and trends in the field.
Download or read book Kernel Adaptive Filtering written by Weifeng Liu and published by John Wiley & Sons. This book was released on 2011-09-20 with total page 167 pages. Available in PDF, EPUB and Kindle. Book excerpt: Online learning from a signal processing perspective There is increased interest in kernel learning algorithms in neural networks and a growing need for nonlinear adaptive algorithms in advanced signal processing, communications, and controls. Kernel Adaptive Filtering is the first book to present a comprehensive, unifying introduction to online learning algorithms in reproducing kernel Hilbert spaces. Based on research being conducted in the Computational Neuro-Engineering Laboratory at the University of Florida and in the Cognitive Systems Laboratory at McMaster University, Ontario, Canada, this unique resource elevates the adaptive filtering theory to a new level, presenting a new design methodology of nonlinear adaptive filters. Covers the kernel least mean squares algorithm, kernel affine projection algorithms, the kernel recursive least squares algorithm, the theory of Gaussian process regression, and the extended kernel recursive least squares algorithm Presents a powerful model-selection method called maximum marginal likelihood Addresses the principal bottleneck of kernel adaptive filters—their growing structure Features twelve computer-oriented experiments to reinforce the concepts, with MATLAB codes downloadable from the authors' Web site Concludes each chapter with a summary of the state of the art and potential future directions for original research Kernel Adaptive Filtering is ideal for engineers, computer scientists, and graduate students interested in nonlinear adaptive systems for online applications (applications where the data stream arrives one sample at a time and incremental optimal solutions are desirable). It is also a useful guide for those who look for nonlinear adaptive filtering methodologies to solve practical problems.
Download or read book Computer Vision ECCV 2022 written by Shai Avidan and published by Springer Nature. This book was released on 2022-11-02 with total page 812 pages. Available in PDF, EPUB and Kindle. Book excerpt: The 39-volume set, comprising the LNCS books 13661 until 13699, constitutes the refereed proceedings of the 17th European Conference on Computer Vision, ECCV 2022, held in Tel Aviv, Israel, during October 23–27, 2022. The 1645 papers presented in these proceedings were carefully reviewed and selected from a total of 5804 submissions. The papers deal with topics such as computer vision; machine learning; deep neural networks; reinforcement learning; object recognition; image classification; image processing; object detection; semantic segmentation; human pose estimation; 3d reconstruction; stereo vision; computational photography; neural networks; image coding; image reconstruction; object recognition; motion estimation.
Download or read book FUSION written by and published by . This book was released on 2000 with total page 834 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Advances in Natural Computation written by Ke Chen and published by Springer Science & Business Media. This book was released on 2005-08-17 with total page 1360 pages. Available in PDF, EPUB and Kindle. Book excerpt: Annotation The three volume set LNCS 3610, LNCS 3611, and LNCS 3612 constitutes the refereed proceedings of the First International Conference on Natural Computation, ICNC 2005, held in Changsha, China, in August 2005 as a joint event in federation with the Second International Conference on Fuzzy Systems and Knowledge Discovery FSKD 2005 (LNAI volumes 3613 and 3614). The program committee selected 313 carefully revised full papers and 189 short papers for presentation in three volumes from 1887 submissions. The first volume includes all the contributions related to learning algorithms and architectures in neural networks, neurodynamics, statistical neural network models and support vector machines, and other topics in neural network models; cognitive science, neuroscience informatics, bioinformatics, and bio-medical engineering, and neural network applications as communications and computer networks, expert system and informatics, and financial engineering. The second volume concentrates on neural network applications such as pattern recognition and diagnostics, robotics and intelligent control, signal processing and multi-media, and other neural network applications; evolutionary learning, artificial immune systems, evolutionary theory, membrane, molecular, DNA computing, and ant colony systems. The third volume deals with evolutionary methodology, quantum computing, swarm intelligence and intelligent agents; natural computation applications as bioinformatics and bio-medical engineering, robotics and intelligent control, and other applications of natural computation; hardware implementations of natural computation, and fuzzy neural systems as well as soft computing.
Download or read book Advances in Natural Computation written by Lipo Wang and published by Springer. This book was released on 2005-08-25 with total page 1350 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book and its sister volumes, i.e., LNCS vols. 3610, 3611, and 3612, are the proceedings of the 1st International Conference on Natural Computation (ICNC 2005), jointly held with the 2nd International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2005, LNAI vols. 3613 and 3614) from 27 to 29 August 2005 in Changsha, Hunan, China.
Download or read book Computer Supported Cooperative Work and Social Computing written by Yuqing Sun and published by Springer Nature. This book was released on 2021-05-06 with total page 725 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed post-conference proceedings of the 15th CCF Conference on Computer Supported Cooperative Work and Social Computing, ChineseCSCW 2020, held in Shenzhen, China, in November 2020. The 40 revised full papers and 15 revised short papers were carefully reviewed and selected from 137 submissions. The papers of this volume are organized in topical sections on: crowdsourcing, crowd intelligence, and crowd cooperative computing; domain-specific collaborative applications; collaborative mechanisms, models, approaches, algorithms, and systems; social media and online communities; and short papers.
Download or read book Multivariate Statistical Machine Learning Methods for Genomic Prediction written by Osval Antonio Montesinos López and published by Springer Nature. This book was released on 2022-02-14 with total page 707 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is open access under a CC BY 4.0 license This open access book brings together the latest genome base prediction models currently being used by statisticians, breeders and data scientists. It provides an accessible way to understand the theory behind each statistical learning tool, the required pre-processing, the basics of model building, how to train statistical learning methods, the basic R scripts needed to implement each statistical learning tool, and the output of each tool. To do so, for each tool the book provides background theory, some elements of the R statistical software for its implementation, the conceptual underpinnings, and at least two illustrative examples with data from real-world genomic selection experiments. Lastly, worked-out examples help readers check their own comprehension.The book will greatly appeal to readers in plant (and animal) breeding, geneticists and statisticians, as it provides in a very accessible way the necessary theory, the appropriate R code, and illustrative examples for a complete understanding of each statistical learning tool. In addition, it weighs the advantages and disadvantages of each tool.
Download or read book Nuclear Science Abstracts written by and published by . This book was released on 1975 with total page 764 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Multisensor Fusion and Integration in the Wake of Big Data Deep Learning and Cyber Physical System written by Sukhan Lee and published by Springer. This book was released on 2018-07-04 with total page 306 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book includes selected papers from the 13th IEEE International Conference on Multisensor Integration and Fusion for Intelligent Systems (MFI 2017) held in Daegu, Korea, November 16–22, 2017. It covers various topics, including sensor/actuator networks, distributed and cloud architectures, bio-inspired systems and evolutionary approaches, methods of cognitive sensor fusion, Bayesian approaches, fuzzy systems and neural networks, biomedical applications, autonomous land, sea and air vehicles, localization, tracking, SLAM, 3D perception, manipulation with multifinger hands, robotics, micro/nano systems, information fusion and sensors, and multimodal integration in HCI and HRI. The book is intended for robotics scientists, data and information fusion scientists, researchers and professionals at universities, research institutes and laboratories.
Download or read book Pattern Recognition and Computer Vision written by Qingshan Liu and published by Springer Nature. This book was released on 2024-01-26 with total page 534 pages. Available in PDF, EPUB and Kindle. Book excerpt: The 13-volume set LNCS 14425-14437 constitutes the refereed proceedings of the 6th Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2023, held in Xiamen, China, during October 13–15, 2023. The 532 full papers presented in these volumes were selected from 1420 submissions. The papers have been organized in the following topical sections: Action Recognition, Multi-Modal Information Processing, 3D Vision and Reconstruction, Character Recognition, Fundamental Theory of Computer Vision, Machine Learning, Vision Problems in Robotics, Autonomous Driving, Pattern Classification and Cluster Analysis, Performance Evaluation and Benchmarks, Remote Sensing Image Interpretation, Biometric Recognition, Face Recognition and Pose Recognition, Structural Pattern Recognition, Computational Photography, Sensing and Display Technology, Video Analysis and Understanding, Vision Applications and Systems, Document Analysis and Recognition, Feature Extraction and Feature Selection, Multimedia Analysis and Reasoning, Optimization and Learning methods, Neural Network and Deep Learning, Low-Level Vision and Image Processing, Object Detection, Tracking and Identification, Medical Image Processing and Analysis.
