Download or read book Multi modal Image Reconstruction by Bayesian Methods written by Xiaolong Ouyang and published by . This book was released on 1993 with total page 378 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Neural Masses and Fields Modelling the Dynamics of Brain Activity written by Karl Friston and published by Frontiers Media SA. This book was released on 2015-05-25 with total page 238 pages. Available in PDF, EPUB and Kindle. Book excerpt: Biophysical modelling of brain activity has a long and illustrious history and has recently profited from technological advances that furnish neuroimaging data at an unprecedented spatiotemporal resolution. Neuronal modelling is a very active area of research, with applications ranging from the characterization of neurobiological and cognitive processes, to constructing artificial brains in silico and building brain-machine interface and neuroprosthetic devices. Biophysical modelling has always benefited from interdisciplinary interactions between different and seemingly distant fields; ranging from mathematics and engineering to linguistics and psychology. This Research Topic aims to promote such interactions by promoting papers that contribute to a deeper understanding of neural activity as measured by fMRI or electrophysiology. In general, mean field models of neural activity can be divided into two classes: neural mass and neural field models. The main difference between these classes is that field models prescribe how a quantity characterizing neural activity (such as average depolarization of a neural population) evolves over both space and time as opposed to mass models, which characterize activity over time only; by assuming that all neurons in a population are located at (approximately) the same point. This Research Topic focuses on both classes of models and considers several aspects and their relative merits that: span from synapses to the whole brain; comparisons of their predictions with EEG and MEG spectra of spontaneous brain activity; evoked responses, seizures, and fitting data - to infer brain states and map physiological parameters.
Download or read book Proceedings of the International e Conference on Intelligent Systems and Signal Processing written by Falgun Thakkar and published by Springer Nature. This book was released on 2021-08-13 with total page 799 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides insights into the Third International Conference on Intelligent Systems and Signal Processing (eISSP 2020) held By Electronics & Communication Engineering Department of G H Patel College of Engineering & Technology, Gujarat, India, during 28–30 December 2020. The book comprises contributions by the research scholars and academicians covering the topics in signal processing and communication engineering, applied electronics and emerging technologies, Internet of Things (IoT), robotics, machine learning, deep learning and artificial intelligence. The main emphasis of the book is on dissemination of information, experience and research results on the current topics of interest through in-depth discussions and contribution of researchers from all over world. The book is useful for research community, academicians, industrialists and postgraduate students across the globe.
Download or read book Multimodal Interaction in Image and Video Applications written by Angel D. Sappa and published by Springer Science & Business Media. This book was released on 2013-01-11 with total page 209 pages. Available in PDF, EPUB and Kindle. Book excerpt: Traditional Pattern Recognition (PR) and Computer Vision (CV) technologies have mainly focused on full automation, even though full automation often proves elusive or unnatural in many applications, where the technology is expected to assist rather than replace the human agents. However, not all the problems can be automatically solved being the human interaction the only way to tackle those applications. Recently, multimodal human interaction has become an important field of increasing interest in the research community. Advanced man-machine interfaces with high cognitive capabilities are a hot research topic that aims at solving challenging problems in image and video applications. Actually, the idea of computer interactive systems was already proposed on the early stages of computer science. Nowadays, the ubiquity of image sensors together with the ever-increasing computing performance has open new and challenging opportunities for research in multimodal human interaction. This book aims to show how existing PR and CV technologies can naturally evolve using this new paradigm. The chapters of this book show different successful case studies of multimodal interactive technologies for both image and video applications. They cover a wide spectrum of applications, ranging from interactive handwriting transcriptions to human-robot interactions in real environments.
Download or read book Multi Level Bayesian Models for Environment Perception written by Csaba Benedek and published by Springer Nature. This book was released on 2022-04-18 with total page 208 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book deals with selected problems of machine perception, using various 2D and 3D imaging sensors. It proposes several new original methods, and also provides a detailed state-of-the-art overview of existing techniques for automated, multi-level interpretation of the observed static or dynamic environment. To ensure a sound theoretical basis of the new models, the surveys and algorithmic developments are performed in well-established Bayesian frameworks. Low level scene understanding functions are formulated as various image segmentation problems, where the advantages of probabilistic inference techniques such as Markov Random Fields (MRF) or Mixed Markov Models are considered. For the object level scene analysis, the book mainly relies on the literature of Marked Point Process (MPP) approaches, which consider strong geometric and prior interaction constraints in object population modeling. In particular, key developments are introduced in the spatial hierarchical decomposition of the observed scenarios, and in the temporal extension of complex MRF and MPP models. Apart from utilizing conventional optical sensors, case studies are provided on passive radar (ISAR) and Lidar-based Bayesian environment perception tasks. It is shown, via several experiments, that the proposed contributions embedded into a strict mathematical toolkit can significantly improve the results in real world 2D/3D test images and videos, for applications in video surveillance, smart city monitoring, autonomous driving, remote sensing, and optical industrial inspection.
Download or read book Bayesian Methods for Multi modal Posterior Topologies written by Biljana Jonoska Stojkova and published by . This book was released on 2017 with total page 107 pages. Available in PDF, EPUB and Kindle. Book excerpt: The purpose of this thesis is to develop efficient Bayesian methods to address multi-modality in posterior topologies. In Chapter 2 we develop a new general Bayesian methodology that simultaneously estimates parameters of interest and probability of the model. The proposed methodology builds on the Simulated Tempering algorithm, which is a powerful sampling algorithm that handles multi-modal distributions, but it is difficult to use in practice due to the requirement to choose suitable prior for the temperature and temperature schedule. Our proposed algorithm removes this requirement, while preserving the sampling efficiency of the Simulated Tempering algorithm. We illustrate the applicability of the new algorithm to different examples involving mixture models of Gaussian distributions and ordinary differential equation models. Chapter 3 proposes a general optimization strategy, which combines results from different optimization or parameter estimation methods to overcome shortcomings of a single method. Embedding the proposed optimization strategy in the Incremental Mixture Importance Sampling with Optimization algorithm (IMIS-Opt) significantly improves sampling efficiency and removes the dependence on the choice of the prior of the IMIS-Opt. We demonstrate that the resulting algorithm provides accurate parameter estimates, while the IMIS-Opt gets trapped in a local mode in the case of the ordinary differential equation (ODE) models. Finally, the resulting algorithm is implemented within the Approximate Bayesian Computation framework to draw likelihood-free inference. Chapter 4 introduces a generalization of the Bayesian Information Criterion (BIC) that handles multi-modality in the posterior space. The BIC is a computationally efficient model selection tool, but it relies on the assumption that the posterior distribution is unimodal. When the posterior is multi-modal the BIC uses only one posterior mode, while discarding the information from the rest of the modes. We demonstrate that the BIC produces inaccurate estimates of the posterior probability of the bimodal model, which in some cases results in the BIC selecting the sub-optimal model. As a remedy, we propose a Multi-modal BIC (MBIC) that incorporates all relevant posterior modes, while preserving the computational efficiency of the BIC. The accuracy of the MBIC is demonstrated through bimodal models and mixture models of Gaussian distributions.
Download or read book Regularization and Bayesian Methods for Inverse Problems in Signal and Image Processing written by Jean-Francois Giovannelli and published by John Wiley & Sons. This book was released on 2015-02-02 with total page 323 pages. Available in PDF, EPUB and Kindle. Book excerpt: The focus of this book is on "ill-posed inverse problems". These problems cannot be solved only on the basis of observed data. The building of solutions involves the recognition of other pieces of a priori information. These solutions are then specific to the pieces of information taken into account. Clarifying and taking these pieces of information into account is necessary for grasping the domain of validity and the field of application for the solutions built. For too long, the interest in these problems has remained very limited in the signal-image community. However, the community has since recognized that these matters are more interesting and they have become the subject of much greater enthusiasm. From the application field’s point of view, a significant part of the book is devoted to conventional subjects in the field of inversion: biological and medical imaging, astronomy, non-destructive evaluation, processing of video sequences, target tracking, sensor networks and digital communications. The variety of chapters is also clear, when we examine the acquisition modalities at stake: conventional modalities, such as tomography and NMR, visible or infrared optical imaging, or more recent modalities such as atomic force imaging and polarized light imaging.
Download or read book Multimodal Brain Image Analysis written by Li Shen and published by Springer. This book was released on 2013-08-15 with total page 268 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the Third International Workshop on Multimodal Brain Image Analysis, MBIA 2013, held in Nagoya, Japan, on September 22, 2013 in conjunction with the 16th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI. The 24 revised full papers presented were carefully reviewed and selected from 35 submissions. The papers are organized in topical sections on analysis, methodologies, algorithms, software systems, validation approaches, benchmark datasets, neuroscience and clinical applications.
Download or read book Maximum Entropy and Bayesian Methods written by Kenneth M. Hanson and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 479 pages. Available in PDF, EPUB and Kindle. Book excerpt: Proceedings of the Fifteenth International Workshop on Maximum Entropy and Bayesian Methods, Santa Fe, New Mexico, USA, 1995
Download or read book Digital Image Processing and Analysis written by Chanda Bhabatosh and published by PHI Learning Pvt. Ltd.. This book was released on 1977 with total page 492 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Multimodal Biometrics and Intelligent Image Processing for Security Systems written by Marina L. Gavrilova and published by IGI Global. This book was released on 2013-03-31 with total page 233 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book provides an in-depth description of existing and fresh fusion approaches for multimodal biometric systems, covering relevant topics affecting the security and intelligent industries"--Provided by publisher.
Download or read book ICDSMLA 2021 written by Amit Kumar and published by Springer Nature. This book was released on 2023-02-06 with total page 875 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gathers selected high-impact articles from the 3rd International Conference on Data Science, Machine Learning & Applications 2021. It highlights the latest developments in the areas of artificial intelligence, machine learning, soft computing, human–computer interaction and various data science and machine learning applications. It brings together scientists and researchers from different universities and industries around the world to showcase a broad range of perspectives, practices and technical expertise.
Download or read book Medical Image Computing and Computer Assisted Intervention MICCAI 2013 written by Kensaku Mori and published by Springer. This book was released on 2013-09-20 with total page 708 pages. Available in PDF, EPUB and Kindle. Book excerpt: The three-volume set LNCS 8149, 8150, and 8151 constitutes the refereed proceedings of the 16th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2013, held in Nagoya, Japan, in September 2013. Based on rigorous peer reviews, the program committee carefully selected 262 revised papers from 789 submissions for presentation in three volumes. The 81 papers included in the third volume have been organized in the following topical sections: image reconstruction and motion modeling; machine learning in medical image computing; imaging, reconstruction, and enhancement; segmentation; physiological modeling, simulation, and planning; intraoperative guidance and robotics; microscope, optical imaging, and histology; diffusion MRI; brain segmentation and atlases; and functional MRI and neuroscience applications.
Download or read book Advanced Image and Video Processing Using MATLAB written by Shengrong Gong and published by Springer. This book was released on 2018-08-21 with total page 596 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers a comprehensive introduction to advanced methods for image and video analysis and processing. It covers deraining, dehazing, inpainting, fusion, watermarking and stitching. It describes techniques for face and lip recognition, facial expression recognition, lip reading in videos, moving object tracking, dynamic scene classification, among others. The book combines the latest machine learning methods with computer vision applications, covering topics such as event recognition based on deep learning,dynamic scene classification based on topic model, person re-identification based on metric learning and behavior analysis. It also offers a systematic introduction to image evaluation criteria showing how to use them in different experimental contexts. The book offers an example-based practical guide to researchers, professionals and graduate students dealing with advanced problems in image analysis and computer vision.
Download or read book Multimodal Brain Image Analysis and Mathematical Foundations of Computational Anatomy written by Dajiang Zhu and published by Springer Nature. This book was released on 2019-10-10 with total page 230 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed joint proceedings of the 4th International Workshop on Multimodal Brain Image Analysis, MBAI 2019, and the 7th International Workshop on Mathematical Foundations of Computational Anatomy, MFCA 2019, held in conjunction with the 22nd International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2019, in Shenzhen, China, in October 2019. The 16 full papers presented at MBAI 2019 and the 7 full papers presented at MFCA 2019 were carefully reviewed and selected. The MBAI papers intend to move forward the state of the art in multimodal brain image analysis, in terms of analysis methodologies, algorithms, software systems, validation approaches, benchmark datasets, neuroscience, and clinical applications. The MFCA papers are devoted to statistical and geometrical methods for modeling the variability of biological shapes. The goal is to foster the interactions between the mathematical community around shapes and the MICCAI community around computational anatomy applications.
Download or read book Multimodal Signal Processing written by Jean-Philippe Thiran and published by Academic Press. This book was released on 2009-11-11 with total page 343 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multimodal signal processing is an important research and development field that processes signals and combines information from a variety of modalities – speech, vision, language, text – which significantly enhance the understanding, modelling, and performance of human-computer interaction devices or systems enhancing human-human communication. The overarching theme of this book is the application of signal processing and statistical machine learning techniques to problems arising in this multi-disciplinary field. It describes the capabilities and limitations of current technologies, and discusses the technical challenges that must be overcome to develop efficient and user-friendly multimodal interactive systems. With contributions from the leading experts in the field, the present book should serve as a reference in multimodal signal processing for signal processing researchers, graduate students, R&D engineers, and computer engineers who are interested in this emerging field. - Presents state-of-art methods for multimodal signal processing, analysis, and modeling - Contains numerous examples of systems with different modalities combined - Describes advanced applications in multimodal Human-Computer Interaction (HCI) as well as in computer-based analysis and modelling of multimodal human-human communication scenes.
Download or read book Pattern Recognition written by Zeynep Akata and published by Springer Nature. This book was released on 2021-03-16 with total page 504 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 42nd German Conference on Pattern Recognition, DAGM GCPR 2020, which took place during September 28 until October 1, 2020. The conference was planned to take place in Tübingen, Germany, but had to change to an online format due to the COVID-19 pandemic. The 34 papers presented in this volume were carefully reviewed and selected from a total of 89 submissions. They were organized in topical sections named: Normalizing Flow, Semantics, Physics, Camera Calibration and Computer Vision, Pattern Recognition, Machine Learning.
