Multimodal Scene Understanding

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

Produk Detail:

  • Author : Michael Yang
  • Publisher : Academic Press
  • Pages : 422 pages
  • ISBN : 0128173599
  • Rating : 4/5 from 21 reviews
CLICK HERE TO GET THIS BOOKMultimodal Scene Understanding

Multimodal Scene Understanding

Multimodal Scene Understanding
  • Author : Michael Yang,Bodo Rosenhahn,Vittorio Murino
  • Publisher : Academic Press
  • Release : 16 July 2019
GET THIS BOOKMultimodal Scene Understanding

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

Multimodal Computational Attention for Scene Understanding and Robotics

Multimodal Computational Attention for Scene Understanding and Robotics
  • Author : Boris Schauerte
  • Publisher : Springer
  • Release : 11 May 2016
GET THIS BOOKMultimodal Computational Attention for Scene Understanding and Robotics

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

Machine Learning for Multimodal Interaction

Machine Learning for Multimodal Interaction
  • Author : Andrei Popescu-Belis,Steve Renals,Hervé Bourlard
  • Publisher : Springer
  • Release : 22 February 2008
GET THIS BOOKMachine Learning for Multimodal Interaction

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

Real-time Multimodal Semantic Scene Understanding for Autonomous UGV Navigation

Real-time Multimodal Semantic Scene Understanding for Autonomous UGV Navigation
  • Author : Yifei Zhang
  • Publisher : Unknown Publisher
  • Release : 04 July 2022
GET THIS BOOKReal-time Multimodal Semantic Scene Understanding for Autonomous UGV Navigation

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

Multimodal Behavior Analysis in the Wild

Multimodal Behavior Analysis in the Wild
  • Author : Xavier Alameda-Pineda,Elisa Ricci,Nicu Sebe
  • Publisher : Academic Press
  • Release : 13 November 2018
GET THIS BOOKMultimodal Behavior Analysis in the Wild

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),

Handbook of Deep Learning Applications

Handbook of Deep Learning Applications
  • Author : Valentina Emilia Balas,Sanjiban Sekhar Roy,Dharmendra Sharma,Pijush Samui
  • Publisher : Springer
  • Release : 25 February 2019
GET THIS BOOKHandbook of Deep Learning Applications

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

Transactions on Pattern Languages of Programming III

Transactions on Pattern Languages of Programming III
  • Author : James Noble,Ralph Johnson,Uwe Zdun,Eugene Wallingford
  • Publisher : Springer
  • Release : 31 May 2013
GET THIS BOOKTransactions on Pattern Languages of Programming III

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

Computer Vision – ECCV 2020

Computer Vision – ECCV 2020
  • Author : Andrea Vedaldi,Horst Bischof,Thomas Brox,Jan-Michael Frahm
  • Publisher : Springer Nature
  • Release : 06 November 2020
GET THIS BOOKComputer Vision – ECCV 2020

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;

2016 International Symposium on Experimental Robotics

2016 International Symposium on Experimental Robotics
  • Author : Dana Kulić,Yoshihiko Nakamura,Oussama Khatib,Gentiane Venture
  • Publisher : Springer
  • Release : 20 March 2017
GET THIS BOOK2016 International Symposium on Experimental Robotics

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

Computer Vision for Microscopy Image Analysis

Computer Vision for Microscopy Image Analysis
  • Author : Mei Chen
  • Publisher : Academic Press
  • Release : 01 December 2020
GET THIS BOOKComputer Vision for Microscopy Image Analysis

Are you a computer scientist working on image analysis? Are you a biologist seeking tools to process the microscopy data from image-based experiments? Computer Vision for Microscopy Image Analysis provides a comprehensive and in-depth discussion of modern computer vision techniques, in particular deep learning, for microscopy image analysis that will advance your efforts. Progress in imaging techniques has enabled the acquisition of large volumes of microscopy data and made it possible to conduct large-scale, image-based experiments for biomedical discovery. The

Vision Models for High Dynamic Range and Wide Colour Gamut Imaging

Vision Models for High Dynamic Range and Wide Colour Gamut Imaging
  • Author : Marcelo Bertalmío
  • Publisher : Academic Press
  • Release : 06 November 2019
GET THIS BOOKVision Models for High Dynamic Range and Wide Colour Gamut Imaging

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

Spectral Geometry of Shapes

Spectral Geometry of Shapes
  • Author : Jing Hua,Zichun Zhong
  • Publisher : Academic Press
  • Release : 15 January 2020
GET THIS BOOKSpectral Geometry of Shapes

Spectral Geometry of Shapes presents unique shape analysis approaches based on shape spectrum in differential geometry. It provides insights on how to develop geometry-based methods for 3D shape analysis. The book is an ideal learning resource for graduate students and researchers in computer science, computer engineering and applied mathematics who have an interest in 3D shape analysis, shape motion analysis, image analysis, medical image analysis, computer vision and computer graphics. Due to the rapid advancement of 3D acquisition technologies there

The Technology of Binaural Understanding

The Technology of Binaural Understanding
  • Author : Jens Blauert,Jonas Braasch
  • Publisher : Springer Nature
  • Release : 12 August 2020
GET THIS BOOKThe Technology of Binaural Understanding

Sound, devoid of meaning, would not matter to us. It is the information sound conveys that helps the brain to understand its environment. Sound and its underlying meaning are always associated with time and space. There is no sound without spatial properties, and the brain always organizes this information within a temporal–spatial framework. This book is devoted to understanding the importance of meaning for spatial and related further aspects of hearing, including cross-modal inference. People, when exposed to acoustic

Metaheuristics in Machine Learning: Theory and Applications

Metaheuristics in Machine Learning: Theory and Applications
  • Author : Diego Oliva
  • Publisher : Springer Nature
  • Release : 04 July 2022
GET THIS BOOKMetaheuristics in Machine Learning: Theory and Applications

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