Semantic Networks For Understanding Scenes
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Semantic Networks For Understanding Scenes
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Author : Gerhard Sagerer
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-06-29
Semantic Networks For Understanding Scenes written by Gerhard Sagerer and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-06-29 with Computers categories.
Figure 1.1. An outdoor scene "A bus is passing three cars which are parking between trees at the side of the road. Houses having two storeys are lined up at the street. 3 4 Introduction Figure 1.2. An assembly scene There seems to be a small open place between the group of houses in the foreground and the store in the background". In such or a similar way the content of the natural scene shown above can be described. It is quite easy to give such a short description. The problem is somewhat more complex for the second image. First of all, it can be stated that the image does not show an everyday scene. It appears as a kind of man made surrounding. But everyone can accept the following statements about this image: 1. The image shows a snapshot of an assembly line. 2. The robot in front is screwing. 3. There is no person in the working area of the robots. 4. All objects on the conveyor belt are worked on by robots. There are no free objects on the belt.
Multimodal Scene Understanding
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Author : Michael Ying Yang
language : en
Publisher: Academic Press
Release Date : 2019-07-16
Multimodal Scene Understanding written by Michael Ying Yang and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-07-16 with Technology & Engineering categories.
Multimodal Scene Understanding: Algorithms, Applications and Deep Learning presents recent advances in multi-modal computing, with a focus on computer vision and photogrammetry. It provides the latest algorithms and applications that involve combining multiple sources of information and 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, thus helping foster interdisciplinary interaction and collaboration between these realms. 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 will find this book to be very useful. - Contains state-of-the-art developments on multi-modal computing - Shines a focus on algorithms and applications - Presents novel deep learning topics on multi-sensor fusion and multi-modal deep learning
Semantic Networks For Understanding Scenes
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Author : Gerhard Sagerer
language : en
Publisher:
Release Date : 2014-01-15
Semantic Networks For Understanding Scenes written by Gerhard Sagerer and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-01-15 with categories.
Semantic Network Analysis In Social Sciences
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Author : Elad Segev
language : en
Publisher: Routledge
Release Date : 2021-11-29
Semantic Network Analysis In Social Sciences written by Elad Segev and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-29 with Psychology categories.
Semantic Network Analysis in Social Sciences introduces the fundamentals of semantic network analysis and its applications in the social sciences. Readers learn how to easily transform any given text into a visual network of words co-occurring together, a process that allows mapping the main themes appearing in the text and revealing its main narratives and biases. Semantic network analysis is particularly useful today with the increasing volumes of text-based information available. It is one of the developing, cutting-edge methods to organize, identify patterns and structures, and understand the meanings of our information society. The first chapters in this book offer step-by-step guidelines for conducting semantic network analysis, including choosing and preparing the text, selecting desired words, constructing the networks, and interpreting their meanings. Free software tools and code are also presented. The rest of the book displays state-of-the-art studies from around the world that apply this method to explore news, political speeches, social media content, and even to organize interview transcripts and literature reviews. Aimed at scholars with no previous knowledge in the field, this book can be used as a main or a supplementary textbook for general courses on research methods or network analysis courses, as well as a starting point to conduct your own content analysis of large texts.
Intelligent Scene Modelling Information Systems
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Author : Georgios Miaoulis
language : en
Publisher: Springer Science & Business Media
Release Date : 2009-03-06
Intelligent Scene Modelling Information Systems written by Georgios Miaoulis and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-03-06 with Computers categories.
This book is dedicated to and contains the latest research in intelligent scene modelling information systems. Declarative scene modeling techniques are presented, as well as their implementation in an intelligent information system.
Graph Neural Network Methods And Applications In Scene Understanding
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Author : Weibin Liu
language : en
Publisher: Springer Nature
Release Date : 2025-01-03
Graph Neural Network Methods And Applications In Scene Understanding written by Weibin Liu and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-03 with Computers categories.
The book focuses on graph neural network methods and applications for scene understanding. Graph Neural Network is an important method for graph-structured data processing, which has strong capability of graph data learning and structural feature extraction. Scene understanding is one of the research focuses in computer vision and image processing, which realizes semantic segmentation and object recognition of image or video. In this book, the algorithm, system design and performance evaluation of scene understanding based on graph neural networks have been studied. First, the book elaborates the background and basic concepts of graph neural network and scene understanding, then introduces the operation mechanism and key methodological foundations of graph neural network. The book then comprehensively explores the implementation and architectural design of graph neural networks for scene understanding tasks, including scene parsing, human parsing, and video object segmentation. The aim of this book is to provide timely coverage of the latest advances and developments in graph neural networks and their applications to scene understanding, particularly for readers interested in research and technological innovation in machine learning, graph neural networks and computer vision. Features of the book include self-supervised feature fusion based graph convolutional network is designed for scene parsing, structure-property based graph representation learning is developed for human parsing, dynamic graph convolutional network based on multi-label learning is designed for human parsing, and graph construction and graph neural network with transformer are proposed for video object segmentation.
Representations And Techniques For 3d Object Recognition And Scene Interpretation
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Author : Derek Hoiem
language : en
Publisher: Springer Nature
Release Date : 2022-05-31
Representations And Techniques For 3d Object Recognition And Scene Interpretation written by Derek Hoiem and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-31 with Computers categories.
One of the grand challenges of artificial intelligence is to enable computers to interpret 3D scenes and objects from imagery. This book organizes and introduces major concepts in 3D scene and object representation and inference from still images, with a focus on recent efforts to fuse models of geometry and perspective with statistical machine learning. The book is organized into three sections: (1) Interpretation of Physical Space; (2) Recognition of 3D Objects; and (3) Integrated 3D Scene Interpretation. The first discusses representations of spatial layout and techniques to interpret physical scenes from images. The second section introduces representations for 3D object categories that account for the intrinsically 3D nature of objects and provide robustness to change in viewpoints. The third section discusses strategies to unite inference of scene geometry and object pose and identity into a coherent scene interpretation. Each section broadly surveys important ideas from cognitive science and artificial intelligence research, organizes and discusses key concepts and techniques from recent work in computer vision, and describes a few sample approaches in detail. Newcomers to computer vision will benefit from introductions to basic concepts, such as single-view geometry and image classification, while experts and novices alike may find inspiration from the book's organization and discussion of the most recent ideas in 3D scene understanding and 3D object recognition. Specific topics include: mathematics of perspective geometry; visual elements of the physical scene, structural 3D scene representations; techniques and features for image and region categorization; historical perspective, computational models, and datasets and machine learning techniques for 3D object recognition; inferences of geometrical attributes of objects, such as size and pose; and probabilistic and feature-passing approaches for contextual reasoning about 3D objects and scenes. Table of Contents: Background on 3D Scene Models / Single-view Geometry / Modeling the Physical Scene / Categorizing Images and Regions / Examples of 3D Scene Interpretation / Background on 3D Recognition / Modeling 3D Objects / Recognizing and Understanding 3D Objects / Examples of 2D 1/2 Layout Models / Reasoning about Objects and Scenes / Cascades of Classifiers / Conclusion and Future Directions
Automatic Extraction Of Man Made Objects From Aerial And Satellite Images Iii
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Author : E.P. Baltsavias
language : en
Publisher: CRC Press
Release Date : 2001-01-01
Automatic Extraction Of Man Made Objects From Aerial And Satellite Images Iii written by E.P. Baltsavias and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001-01-01 with Computers categories.
This work is a collection of papers from the world's leading research groups in the field of automatic extraction of objects, especially buildings and roads, from aerial and space imagery, including new sensors like SAR and lidar.
Visual Information Processing
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Author :
language : en
Publisher:
Release Date : 2006
Visual Information Processing written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006 with Image processing categories.
The Semantics Of English Prepositions
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Author : Andrea Tyler
language : en
Publisher: Cambridge University Press
Release Date : 2003-06-05
The Semantics Of English Prepositions written by Andrea Tyler and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003-06-05 with Language Arts & Disciplines categories.
Using a cognitive linguistics perspective, this book provides a comprehensive, theoretical analysis of the semantics of English prepositions. All English prepositions originally coded spatial relations between two physical entities; while retaining their original meaning, prepositions have also developed a rich set of non-spatial meanings. In this study, Tyler and Evans argue that all these meanings are systematically grounded in the nature of human spatio-physical experience. The original 'spatial scenes' provide the foundation for the extension of meaning from the spatial to the more abstract. This analysis articulates an alternative methodology that distinguishes between a conventional meaning and an interpretation produced for understanding the preposition in context, as well as establishing which of several competing senses should be taken as the primary sense. Together, the methodology and framework are sufficiently articulated to generate testable predictions and allow the analysis to be applied to additional prepositions.