Multimodal Computational Attention for Scene Understanding and Robotics, Schauerte Boris
Автор: Boris Schauerte Название: Multimodal Computational Attention for Scene Understanding and Robotics ISBN: 3319337947 ISBN-13(EAN): 9783319337944 Издательство: Springer Рейтинг: Цена: 121890.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book presents state-of-the-art computationalattention models that have been successfully tested in diverse applicationareas and can build the foundation for artificial systems to efficientlyexplore, analyze, and understand natural scenes.
Автор: Yang, Michael Название: Multimodal Scene Understanding ISBN: 0128173580 ISBN-13(EAN): 9780128173589 Издательство: Elsevier Science Рейтинг: Цена: 123520.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
Multimodal Scene Understanding: Algorithms, Applications and Deep Learning presents recent advances in multi-modal computing, with a focus on computer vision and photogrammetry, providing the latest algorithms and applications that involve combining multiple sources of information. Uniquely, it describes the role and approaches of multi-sensory data and multi-modal deep learning.
The book is ideal for researchers from the fields of computer vision, remote sensing, robotics, and photogrammetry, helping to foster interdisciplinary interaction and collaboration between them. It will be very relevant to researchers collecting and analyzing multi-sensory data collections - for example, KITTI benchmark (stereo+laser) - from different platforms, such as autonomous vehicles, surveillance cameras, UAVs, planes and satellites.
Contains State-of-the-art development on multi-modal computing
A focus on algorithms and applications
Gives novel deep learning topics on multi-sensor fusion
Presents Multi-modal deep learning
Название: Image Understanding: Advances In Computational Vision Volume 2 ISBN: 0893913111 ISBN-13(EAN): 9780893913113 Издательство: Elsevier Science Рейтинг: Цена: 70250.00 T Наличие на складе: Невозможна поставка. Описание: The volumes in this series contain studies in computational vision or "image understanding", and explain the computations that underlie the extraction and use of visual information by both biological and artificial systems. Reprints of seminal studies are included along with the original articles.
Название: Image Understanding: Advances In Computational Vision Volume 3 ISBN: 0893915475 ISBN-13(EAN): 9780893915476 Издательство: Elsevier Science Рейтинг: Цена: 67790.00 T Наличие на складе: Невозможна поставка. Описание: The volumes in this series contain studies in computational vision or "image understanding", and explain the computations that underlie the extraction and use of visual information by both biological and artificial systems. Reprints of seminal studies are included along with the original articles.
Автор: Nie Liqiang, Liu Meng, Song Xuemeng Название: Multimodal Learning toward Micro-Video Understanding ISBN: 1681736284 ISBN-13(EAN): 9781681736280 Издательство: Mare Nostrum (Eurospan) Цена: 82230.00 T Наличие на складе: Нет в наличии. Описание:
Micro-videos, a new form of user-generated content, have been spreading widely across various social platforms, such as Vine, Kuaishou, and TikTok.
Different from traditional long videos, micro-videos are usually recorded by smart mobile devices at any place within a few seconds. Due to their brevity and low bandwidth cost, micro-videos are gaining increasing user enthusiasm. The blossoming of micro-videos opens the door to the possibility of many promising applications, ranging from network content caching to online advertising. Thus, it is highly desirable to develop an effective scheme for high-order micro-video understanding.
Micro-video understanding is, however, non-trivial due to the following challenges: (1) how to represent micro-videos that only convey one or few high-level themes or concepts; (2) how to utilize the hierarchical structure of venue categories to guide micro-video analysis; (3) how to alleviate the influence of low quality caused by complex surrounding environments and camera shake; (4) how to model multimodal sequential data, i.e. textual, acoustic, visual, and social modalities to enhance micro-video understanding; and (5) how to construct large-scale benchmark datasets for analysis. These challenges have been largely unexplored to date.
In this book, we focus on addressing the challenges presented above by proposing some state-of-the-art multimodal learning theories. To demonstrate the effectiveness of these models, we apply them to three practical tasks of micro-video understanding: popularity prediction, venue category estimation, and micro-video routing. Particularly, we first build three large-scale real-world micro-video datasets for these practical tasks. We then present a multimodal transductive learning framework for micro-video popularity prediction. Furthermore, we introduce several multimodal cooperative learning approaches and a multimodal transfer learning scheme for micro-video venue category estimation. Meanwhile, we develop a multimodal sequential learning approach for micro-video recommendation. Finally, we conclude the book and figure out the future research directions in multimodal learning toward micro-video understanding.
Автор: Nie Liqiang, Liu Meng, Song Xuemeng Название: Multimodal Learning toward Micro-Video Understanding ISBN: 1681736306 ISBN-13(EAN): 9781681736303 Издательство: Mare Nostrum (Eurospan) Цена: 103490.00 T Наличие на складе: Нет в наличии. Описание:
Micro-videos, a new form of user-generated content, have been spreading widely across various social platforms, such as Vine, Kuaishou, and TikTok.
Different from traditional long videos, micro-videos are usually recorded by smart mobile devices at any place within a few seconds. Due to their brevity and low bandwidth cost, micro-videos are gaining increasing user enthusiasm. The blossoming of micro-videos opens the door to the possibility of many promising applications, ranging from network content caching to online advertising. Thus, it is highly desirable to develop an effective scheme for high-order micro-video understanding.
Micro-video understanding is, however, non-trivial due to the following challenges: (1) how to represent micro-videos that only convey one or few high-level themes or concepts; (2) how to utilize the hierarchical structure of venue categories to guide micro-video analysis; (3) how to alleviate the influence of low quality caused by complex surrounding environments and camera shake; (4) how to model multimodal sequential data, i.e. textual, acoustic, visual, and social modalities to enhance micro-video understanding; and (5) how to construct large-scale benchmark datasets for analysis. These challenges have been largely unexplored to date.
In this book, we focus on addressing the challenges presented above by proposing some state-of-the-art multimodal learning theories. To demonstrate the effectiveness of these models, we apply them to three practical tasks of micro-video understanding: popularity prediction, venue category estimation, and micro-video routing. Particularly, we first build three large-scale real-world micro-video datasets for these practical tasks. We then present a multimodal transductive learning framework for micro-video popularity prediction. Furthermore, we introduce several multimodal cooperative learning approaches and a multimodal transfer learning scheme for micro-video venue category estimation. Meanwhile, we develop a multimodal sequential learning approach for micro-video recommendation. Finally, we conclude the book and figure out the future research directions in multimodal learning toward micro-video understanding.
Автор: Dajiang Zhu; Jingwen Yan; Heng Huang; Li Shen; Pau Название: Multimodal Brain Image Analysis and Mathematical Foundations of Computational Anatomy ISBN: 303033225X ISBN-13(EAN): 9783030332259 Издательство: Springer Рейтинг: Цена: 54030.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: MBIA.- Non-rigid Registration of White Matter Tractography Using Coherent Point Drift Algorithm.- An Edge Enhanced SRGAN for MRI Super Resolution in Slice-selection Direction.- Exploring Functional Connectivity Biomarker in Autism Using Group-wise Sparse Representation.- Classifying Stages of Mild Cognitive Impairment via Augmented Graph Embedding.- Mapping the spatio-temporal functional coherence in the resting brain.- Species-Preserved Structural Connections Revealed by Sparse Tensor CCA.- Identification of Abnormal Cortical 3-hinge Folding Patterns on Autism Spectral Brains.- Exploring Brain Hemodynamic Response Patterns Via Deep Recurrent Autoencoder.- 3D Convolutional Long-short Term Memory Network for Spatiotemporal Modeling of fMRI Data.- Biological Knowledge Guided Deep Neural Network for Genotype-Phenotype Association Study.- Learning Human Cognition via fMRI Analysis Using 3D CNN and Graph Neural Network.- CU-Net: Cascaded U-Net with Loss Weighted Sampling for Brain Tumor Segmentation.- BrainPainter: A software for the visualisation of brain structures, biomarkers and associated pathological processes.- Structural Similarity based Anatomical and Functional Brain Imaging Fusion.- Multimodal Brain Tumor Segmentation Using Encoder-Decoder with Hierarchical Separable Convolution.- Prioritizing Amyloid Imaging Biomarkers in Alzheimer's Disease via Learning to Rank.- MFCA.- Diffeomorphic Metric Learning and Template Optimization for Registration-Based Predictive Models.- 3D mapping of serial histology sections with anomalies using a novel robust deformable registration algorithm.- Spatiotemporal Modeling for Image Time Series with Appearance Change: Application to Early Brain Development.- Surface Foliation Based Brain Morphometry Analysis.- Mixture Probabilistic Principal Geodesic Analysis.- A Geodesic Mixed Effects Model in Kendall's Shape Space.- An as-invariant-as-possible GL+(3)-based Statistical Shape Model.
Автор: Mancas Название: From Human Attention to Computational Attention ISBN: 1493934333 ISBN-13(EAN): 9781493934331 Издательство: Springer Рейтинг: Цена: 148020.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This both accessible and exhaustive book will help to improve modeling of attention and to inspire innovations in industry. It introduces the study of attention and focuses on attention modeling, addressing such themes as saliency models, signal detection and different types of signals, as well as real-life applications. The book is truly multi-disciplinary, collating work from psychology, neuroscience, engineering and computer science, amongst other disciplines. What is attention? We all pay attention every single moment of our lives. Attention is how the brain selects and prioritizes information. The study of attention has become incredibly complex and divided: this timely volume assists the reader by drawing together work on the computational aspects of attention from across the disciplines. Those working in the field as engineers will benefit from this book’s introduction to the psychological and biological approaches to attention, and neuroscientists can learn about engineering work on attention. The work features practical reviews and chapters that are quick and easy to read, as well as chapters which present deeper, more complex knowledge. Everyone whose work relates to human perception, to image, audio and video processing will find something of value in this book, from students to researchers and those in industry.
Автор: Mancas Matei, Ferrera Vincent P., Riche Nicolas Название: From Human Attention to Computational Attention: A Multidisciplinary Approach ISBN: 1493980505 ISBN-13(EAN): 9781493980505 Издательство: Springer Рейтинг: Цена: 139750.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This both accessible and exhaustive book will help to improve modeling of attention and to inspire innovations in industry. It introduces the study of attention and focuses on attention modeling, addressing such themes as saliency models, signal detection and different types of signals, as well as real-life applications. The book is truly multi-disciplinary, collating work from psychology, neuroscience, engineering and computer science, amongst other disciplines. What is attention? We all pay attention every single moment of our lives. Attention is how the brain selects and prioritizes information. The study of attention has become incredibly complex and divided: this timely volume assists the reader by drawing together work on the computational aspects of attention from across the disciplines. Those working in the field as engineers will benefit from this book’s introduction to the psychological and biological approaches to attention, and neuroscientists can learn about engineering work on attention. The work features practical reviews and chapters that are quick and easy to read, as well as chapters which present deeper, more complex knowledge. Everyone whose work relates to human perception, to image, audio and video processing will find something of value in this book, from students to researchers and those in industry.
Название: Algorithmic and Computational Robotics ISBN: 0367447266 ISBN-13(EAN): 9780367447267 Издательство: Taylor&Francis Рейтинг: Цена: 60220.00 T Наличие на складе: Невозможна поставка. Описание: This book contains the proceedings of the Fourth International Workshop on the Algorithmic Foundations of Robotics (WAFR) to discuss recent trends and important future directions of research on the algorithmic and computational foundations of robotics.
Автор: Yokota, Masao (fukuoka Institute Of Technology, Office B-806, Japan) Название: Natural language understanding and cognitive robotics ISBN: 0367360314 ISBN-13(EAN): 9780367360313 Издательство: Taylor&Francis Рейтинг: Цена: 178640.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The book is aimed at researchers and students interested in artificial intelligence, robotics, or cognitive science. Based on philosophical considerations, this will also have an appeal in linguistics, psychology, ontology, geography, and cartography.
Автор: Sirouspour Название: Advanced Engineering And Computational Methodologies For Intelligent Mecha ISBN: 1466636343 ISBN-13(EAN): 9781466636347 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 189420.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The emergence of mechatronics has advanced the engineering disciplines, producing a plethora of useful technical systems. <br><br><em>Advanced Engineering and Computational Methodologies for Intelligent Mechatronics and Robotics</em> presents the latest innovations and technologies in the fields of mechatronics and robotics. These innovations are applied to a wide range of applications for robotic-assisted manufacturing, complex systems, and many more. This publication is essential to bridge the gap between theory and practice for researchers, engineers, and practitioners from academia to government.
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