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: 18528.00 р. 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
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.
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: 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: 26796.00 р. Наличие на складе: Нет в наличии.
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: Ishwar K. Sethi Название: Computational Vision and Robotics ISBN: 8132221958 ISBN-13(EAN): 9788132221951 Издательство: Springer Рейтинг: Цена: 19564.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The book also covers article from the areas of Robotics such as Solar Power Robot Vehicle, Multi Robot Area Exploration, Intelligent Driving System based on Video Sequencing, Emotion Recognition using MLP Network, Identifying the Unstructured Environment.
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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