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Multimodal Scene Understanding

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Multimodal Scene Understanding

Multimodal Scene Understanding Book
Author : Michael Yang,Bodo Rosenhahn,Vittorio Murino
Publisher : Academic Press
Release : 2019-07-16
ISBN : 0128173599
Language : En, Es, Fr & De

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Book Description :

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

Multimodal Computational Attention for Scene Understanding and Robotics

Multimodal Computational Attention for Scene Understanding and Robotics Book
Author : Boris Schauerte
Publisher : Springer
Release : 2016-05-11
ISBN : 3319337963
Language : En, Es, Fr & De

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Book Description :

This book presents state-of-the-art computational attention models that have been successfully tested in diverse application areas and can build the foundation for artificial systems to efficiently explore, analyze, and understand natural scenes. It gives a comprehensive overview of the most recent computational attention models for processing visual and acoustic input. It covers the biological background of visual and auditory attention, as well as bottom-up and top-down attentional mechanisms and discusses various applications. In the first part new approaches for bottom-up visual and acoustic saliency models are presented and applied to the task of audio-visual scene exploration of a robot. In the second part the influence of top-down cues for attention modeling is investigated.

Multimodal Computational Attention for Scene Understanding

Multimodal Computational Attention for Scene Understanding Book
Author : Boris Schauerte
Publisher : Unknown
Release : 2014
ISBN : 0987650XXX
Language : En, Es, Fr & De

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Book Description :

Download Multimodal Computational Attention for Scene Understanding book written by Boris Schauerte, available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.

Machine Learning for Multimodal Interaction

Machine Learning for Multimodal Interaction Book
Author : Andrei Popescu-Belis,Steve Renals,Hervé Bourlard
Publisher : Springer
Release : 2008-02-22
ISBN : 3540781552
Language : En, Es, Fr & De

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Book Description :

This book constitutes the thoroughly refereed post-proceedings of the 4th International Workshop on Machine Learning for Multimodal Interaction, MLMI 2007, held in Brno, Czech Republic, in June 2007. The 25 revised full papers presented together with 1 invited paper were carefully selected during two rounds of reviewing and revision from 60 workshop presentations. The papers are organized in topical sections on multimodal processing, HCI, user studies and applications, image and video processing, discourse and dialogue processing, speech and audio processing, as well as the PASCAL speech separation challenge.

Real time Multimodal Semantic Scene Understanding for Autonomous UGV Navigation

Real time Multimodal Semantic Scene Understanding for Autonomous UGV Navigation Book
Author : Yifei Zhang
Publisher : Unknown
Release : 2021
ISBN : 0987650XXX
Language : En, Es, Fr & De

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Book Description :

Robust semantic scene understanding is challenging due to complex object types, as well as environmental changes caused by varying illumination and weather conditions. This thesis studies the problem of deep semantic segmentation with multimodal image inputs. Multimodal images captured from various sensory modalities provide complementary information for complete scene understanding. We provided effective solutions for fully-supervised multimodal image segmentation and few-shot semantic segmentation of the outdoor road scene. Regarding the former case, we proposed a multi-level fusion network to integrate RGB and polarimetric images. A central fusion framework was also introduced to adaptively learn the joint representations of modality-specific features and reduce model uncertainty via statistical post-processing.In the case of semi-supervised semantic scene understanding, we first proposed a novel few-shot segmentation method based on the prototypical network, which employs multiscale feature enhancement and the attention mechanism. Then we extended the RGB-centric algorithms to take advantage of supplementary depth cues. Comprehensive empirical evaluations on different benchmark datasets demonstrate that all the proposed algorithms achieve superior performance in terms of accuracy as well as demonstrating the effectiveness of complementary modalities for outdoor scene understanding for autonomous navigation.

Active Vision for Scene Understanding

Active Vision for Scene Understanding Book
Author : Grotz, Markus
Publisher : KIT Scientific Publishing
Release : 2021-12-21
ISBN : 3731511010
Language : En, Es, Fr & De

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Book Description :

Visual perception is one of the most important sources of information for both humans and robots. A particular challenge is the acquisition and interpretation of complex unstructured scenes. This work contributes to active vision for humanoid robots. A semantic model of the scene is created, which is extended by successively changing the robot's view in order to explore interaction possibilities of the scene.

Multimodal Behavior Analysis in the Wild

Multimodal Behavior Analysis in the Wild Book
Author : Xavier Alameda-Pineda,Elisa Ricci,Nicu Sebe
Publisher : Academic Press
Release : 2018-11-13
ISBN : 0128146028
Language : En, Es, Fr & De

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Book Description :

Multimodal Behavioral Analysis in the Wild: Advances and Challenges presents the state-of- the-art in behavioral signal processing using different data modalities, with a special focus on identifying the strengths and limitations of current technologies. The book focuses on audio and video modalities, while also emphasizing emerging modalities, such as accelerometer or proximity data. It covers tasks at different levels of complexity, from low level (speaker detection, sensorimotor links, source separation), through middle level (conversational group detection, addresser and addressee identification), and high level (personality and emotion recognition), providing insights on how to exploit inter-level and intra-level links. This is a valuable resource on the state-of-the- art and future research challenges of multi-modal behavioral analysis in the wild. It is suitable for researchers and graduate students in the fields of computer vision, audio processing, pattern recognition, machine learning and social signal processing. Gives a comprehensive collection of information on the state-of-the-art, limitations, and challenges associated with extracting behavioral cues from real-world scenarios Presents numerous applications on how different behavioral cues have been successfully extracted from different data sources Provides a wide variety of methodologies used to extract behavioral cues from multi-modal data

2016 International Symposium on Experimental Robotics

2016 International Symposium on Experimental Robotics Book
Author : Dana Kulić,Yoshihiko Nakamura,Oussama Khatib,Gentiane Venture
Publisher : Springer
Release : 2017-03-20
ISBN : 3319501151
Language : En, Es, Fr & De

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Book Description :

Experimental Robotics XV is the collection of papers presented at the International Symposium on Experimental Robotics, Roppongi, Tokyo, Japan on October 3-6, 2016. 73 scientific papers were selected and presented after peer review. The papers span a broad range of sub-fields in robotics including aerial robots, mobile robots, actuation, grasping, manipulation, planning and control and human-robot interaction, but shared cutting-edge approaches and paradigms to experimental robotics. The readers will find a breadth of new directions of experimental robotics. The International Symposium on Experimental Robotics is a series of bi-annual symposia sponsored by the International Foundation of Robotics Research, whose goal is to provide a forum dedicated to experimental robotics research. Robotics has been widening its scientific scope, deepening its methodologies and expanding its applications. However, the significance of experiments remains and will remain at the center of the discipline. The ISER gatherings are a venue where scientists can gather and talk about robotics based on this central tenet.

Transactions on Pattern Languages of Programming III

Transactions on Pattern Languages of Programming III Book
Author : James Noble,Ralph Johnson,Uwe Zdun,Eugene Wallingford
Publisher : Springer
Release : 2013-05-31
ISBN : 3642386768
Language : En, Es, Fr & De

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Book Description :

The Transactions on Pattern Languages of Programming subline aims to publish papers on patterns and pattern languages as applied to software design, development, and use, throughout all phases of the software life cycle, from requirements and design to implementation, maintenance and evolution. The primary focus of this LNCS Transactions subline is on patterns, pattern collections, and pattern languages themselves. The journal also includes reviews, survey articles, criticisms of patterns and pattern languages, as well as other research on patterns and pattern languages. This book, the third volume in the Transactions on Pattern Languages of Programming series, presents five papers that have been through a careful peer review process involving both pattern experts and domain experts. The papers present various pattern languages and a study of applying patterns and represent some of the best work that has been carried out in design patterns and pattern languages of programming over the last few years.

Screens and Scenes

Screens and Scenes Book
Author : Richard Kern,Christine Develotte
Publisher : Routledge
Release : 2018-06-21
ISBN : 131544710X
Language : En, Es, Fr & De

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Book Description :

This book examines the relationships between online visual interfaces and language use in educational contexts and the features that underpin them to explore the complex nature of online communication and its implications for educational practice. Adopting a case study approach featuring a global range of examples, the volume uniquely focuses on multimodal intercultural interactions, with a particular interest in videoconferencing, to look at how they project and reflect particular cultural values and tendencies concerning language use and how they elucidate the complex cultural identifications and affiliations inherent in intercultural encounters. The book employs a diverse range of theoretical and research frameworks to highlight the dynamic connections between digital technology, social life, and language use, and the ways in which they can inform language education, making this an ideal resource for students and scholars in applied linguistics, communication studies, media studies, information studies, and education.

Computer Vision ECCV 2020

Computer Vision     ECCV 2020 Book
Author : Andrea Vedaldi,Horst Bischof,Thomas Brox,Jan-Michael Frahm
Publisher : Springer Nature
Release : 2020-11-11
ISBN : 3030585654
Language : En, Es, Fr & De

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Book Description :

The 30-volume set, comprising the LNCS books 12346 until 12375, constitutes the refereed proceedings of the 16th European Conference on Computer Vision, ECCV 2020, which was planned to be held in Glasgow, UK, during August 23-28, 2020. The conference was held virtually due to the COVID-19 pandemic. The 1360 revised papers presented in these proceedings were carefully reviewed and selected from a total of 5025 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.

Vision Models for High Dynamic Range and Wide Colour Gamut Imaging

Vision Models for High Dynamic Range and Wide Colour Gamut Imaging Book
Author : Marcelo Bertalmío
Publisher : Academic Press
Release : 2019-11-06
ISBN : 0128138955
Language : En, Es, Fr & De

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Book Description :

To enhance the overall viewing experience (for cinema, TV, games, AR/VR) the media industry is continuously striving to improve image quality. Currently the emphasis is on High Dynamic Range (HDR) and Wide Colour Gamut (WCG) technologies, which yield images with greater contrast and more vivid colours. The uptake of these technologies, however, has been hampered by the significant challenge of understanding the science behind visual perception. Vision Models for High Dynamic Range and Wide Colour Gamut Imaging provides university researchers and graduate students in computer science, computer engineering, vision science, as well as industry R&D engineers, an insight into the science and methods for HDR and WCG. It presents the underlying principles and latest practical methods in a detailed and accessible way, highlighting how the use of vision models is a key element of all state-of-the-art methods for these emerging technologies. Presents the underlying vision science principles and models that are essential to the emerging technologies of HDR and WCG Explores state-of-the-art techniques for tone and gamut mapping Discusses open challenges and future directions of HDR and WCG research

Handbook of Deep Learning Applications

Handbook of Deep Learning Applications Book
Author : Valentina Emilia Balas,Sanjiban Sekhar Roy,Dharmendra Sharma,Pijush Samui
Publisher : Springer
Release : 2019-02-25
ISBN : 3030114791
Language : En, Es, Fr & De

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Book Description :

This book presents a broad range of deep-learning applications related to vision, natural language processing, gene expression, arbitrary object recognition, driverless cars, semantic image segmentation, deep visual residual abstraction, brain–computer interfaces, big data processing, hierarchical deep learning networks as game-playing artefacts using regret matching, and building GPU-accelerated deep learning frameworks. Deep learning, an advanced level of machine learning technique that combines class of learning algorithms with the use of many layers of nonlinear units, has gained considerable attention in recent times. Unlike other books on the market, this volume addresses the challenges of deep learning implementation, computation time, and the complexity of reasoning and modeling different type of data. As such, it is a valuable and comprehensive resource for engineers, researchers, graduate students and Ph.D. scholars.

Metaheuristics in Machine Learning Theory and Applications

Metaheuristics in Machine Learning  Theory and Applications Book
Author : Diego Oliva
Publisher : Springer Nature
Release : 2022-07-05
ISBN : 3030705420
Language : En, Es, Fr & De

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Book Description :

This book is a collection of the most recent approaches that combine metaheuristics and machine learning. Some of the methods considered in this book are evolutionary, swarm, machine learning, and deep learning. The chapters were classified based on the content; then, the sections are thematic. Different applications and implementations are included; in this sense, the book provides theory and practical content with novel machine learning and metaheuristic algorithms. The chapters were compiled using a scientific perspective. Accordingly, the book is primarily intended for undergraduate and postgraduate students of Science, Engineering, and Computational Mathematics and is useful in courses on Artificial Intelligence, Advanced Machine Learning, among others. Likewise, the book is useful for research from the evolutionary computation, artificial intelligence, and image processing communities.

Proceedings of the Future Technologies Conference FTC 2021 Volume 1

Proceedings of the Future Technologies Conference  FTC  2021  Volume 1 Book
Author : Kohei Arai
Publisher : Springer Nature
Release : 2022-07-05
ISBN : 3030899063
Language : En, Es, Fr & De

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Book Description :

Download Proceedings of the Future Technologies Conference FTC 2021 Volume 1 book written by Kohei Arai, available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.

Cyberspace Data and Intelligence and Cyber Living Syndrome and Health

Cyberspace Data and Intelligence  and Cyber Living  Syndrome  and Health Book
Author : Huansheng Ning,Feifei Shi
Publisher : Springer Nature
Release : 2020-12-01
ISBN : 9813343362
Language : En, Es, Fr & De

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Book Description :

This volume constitutes the proceedings of the Forth International Conference on Cyberspace Data and Intelligence, Cyber DI 2020, and the International Conference on Cyber-Living, Cyber-Syndrome, and Cyber-Health, CyberLife 2020, held under the umbrella of the 2020 Cyberspace Congress, held in Beijing, China, in December 2020.* The 13 full papers presented were carefully reviewed and selected from 36 submissions. The papers are grouped in the following topics: machine learning and ubiquitous and intelligent computing. * The conference was held virtually due to the COVID-19 pandemic.

Artificial Neural Networks and Machine Learning ICANN 2021

Artificial Neural Networks and Machine Learning     ICANN 2021 Book
Author : Igor Farkaš,Paolo Masulli,Sebastian Otte,Stefan Wermter
Publisher : Springer Nature
Release : 2021-09-11
ISBN : 303086362X
Language : En, Es, Fr & De

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Book Description :

The proceedings set LNCS 12891, LNCS 12892, LNCS 12893, LNCS 12894 and LNCS 12895 constitute the proceedings of the 30th International Conference on Artificial Neural Networks, ICANN 2021, held in Bratislava, Slovakia, in September 2021.* The total of 265 full papers presented in these proceedings was carefully reviewed and selected from 496 submissions, and organized in 5 volumes. In this volume, the papers focus on topics such as adversarial machine learning, anomaly detection, attention and transformers, audio and multimodal applications, bioinformatics and biosignal analysis, capsule networks and cognitive models. *The conference was held online 2021 due to the COVID-19 pandemic.

Image Analysis

Image Analysis Book
Author : Puneet Sharma,Filippo Maria Bianchi
Publisher : Springer
Release : 2017-05-22
ISBN : 3319591266
Language : En, Es, Fr & De

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Book Description :

The two-volume set LNCS 10269 and 10270 constitutes the refereed proceedings of the 20th Scandinavian Conference on Image Analysis, SCIA 2017, held in Tromsø, Norway, in June 2017. The 87 revised papers presented were carefully reviewed and selected from 133 submissions. The contributions are structured in topical sections on history of SCIA; motion analysis and 3D vision; pattern detection and recognition; machine learning; image processing and applications; feature extraction and segmentation; remote sensing; medical and biomedical image analysis; faces, gestures and multispectral analysis.

Machine Learning in Computer Vision

Machine Learning in Computer Vision Book
Author : Nicu Sebe,Ira Cohen,Ashutosh Garg,Thomas S. Huang
Publisher : Springer Science & Business Media
Release : 2006-03-30
ISBN : 1402032757
Language : En, Es, Fr & De

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Book Description :

The goal of this book is to address the use of several important machine learning techniques into computer vision applications. An innovative combination of computer vision and machine learning techniques has the promise of advancing the field of computer vision, which contributes to better understanding of complex real-world applications. The effective usage of machine learning technology in real-world computer vision problems requires understanding the domain of application, abstraction of a learning problem from a given computer vision task, and the selection of appropriate representations for the learnable (input) and learned (internal) entities of the system. In this book, we address all these important aspects from a new perspective: that the key element in the current computer revolution is the use of machine learning to capture the variations in visual appearance, rather than having the designer of the model accomplish this. As a bonus, models learned from large datasets are likely to be more robust and more realistic than the brittle all-design models.