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This brief presents new architecture and strategies for
distribution of social video content. A primary framework for
socially-aware video delivery and a thorough overview of the
possible approaches is provided. The book identifies the unique
characteristics of socially-aware video access and social content
propagation, revealing the design and integration of individual
modules that are aimed at enhancing user experience in the social
network context. The change in video content generation,
propagation, and consumption for online social networks, has
significantly challenged the traditional video delivery paradigm.
Given the massive amount of user-generated content shared in online
social networks, users are now engaged as active participants in
the social ecosystem rather than as passive receivers of media
content. This revolution is being driven further by the deep
penetration of 3G/4G wireless networks and smart mobile devices
that are seamlessly integrated with online social networking and
media-sharing services. Despite increasingly abundant bandwidth and
computational resources, the ever-increasing volume of data created
by user-generated video content--along with the boundless coverage
of socialized sharing--presents unprecedented challenges.
Visual Question Answering (VQA) usually combines visual inputs like
image and video with a natural language question concerning the
input and generates a natural language answer as the
output. This is by nature a multi-disciplinary research
problem, involving computer vision (CV), natural language
processing (NLP), knowledge representation and reasoning (KR), etc.
Further, VQA is an ambitious undertaking, as it must overcome the
challenges of general image understanding and the
question-answering task, as well as the difficulties entailed by
using large-scale databases with mixed-quality inputs. However,
with the advent of deep learning (DL) and driven by the existence
of advanced techniques in both CV and NLP and the availability of
relevant large-scale datasets, we have recently seen enormous
strides in VQA, with more systems and promising results emerging.
This book provides a comprehensive overview of VQA, covering
fundamental theories, models, datasets, and promising future
directions. Given its scope, it can be used as a textbook on
computer vision and natural language processing, especially for
researchers and students in the area of visual question answering.
It also highlights the key models used in VQA.
This book disseminates and promotes the recent research progress
and frontier development on AutoML and meta-learning as well as
their applications on computer vision, natural language processing,
multimedia and data mining related fields. These are exciting and
fast-growing research directions in the general field of machine
learning. The authors advocate novel, high-quality research
findings, and innovative solutions to the challenging problems in
AutoML and meta-learning. This topic is at the core of the scope of
artificial intelligence, and is attractive to audience from both
academia and industry. This book is highly accessible to the whole
machine learning community, including: researchers, students and
practitioners who are interested in AutoML, meta-learning, and
their applications in multimedia, computer vision, natural language
processing and data mining related tasks. The book is
self-contained and designed for introductory and intermediate
audiences. No special prerequisite knowledge is required to read
this book.
While most books on the subject focus on resource allocation in
just one type of network, this book is the first to examine the
common characteristics of multiple distributed video communication
systems. Comprehensive and systematic, Optimal Resource Allocation
for Distributed Video Communication presents a unified optimization
framework for resource allocation across these systems. The book
examines the techniques required for optimal resource allocation
over Internet, wireless cellular networks, wireless ad hoc
networks, and wireless sensor networks. It provides you with the
required foundation in video communications, including Peer-to-Peer
(P2P) networks, wireless networks, and visual sensor networks.
Whether you're in industry or academia, you'll value how the book
outlines current challenges facing the field and outlines a general
solution framework for addressing these challenges. From problem
formulations and theoretical analysis to practical algorithms, it
facilitates the comprehensive understanding required to achieve
optimized video and multimedia communications. Presents the
resource allocation techniques for scalable video communications
over Internet or wireless networks Examines two resource allocation
problems-distributed throughput maximization for scalable P2P
Video-on-Demand (VoD) systems and streaming capacity for P2P VoD
systems Outlines an optimal prefetching framework for reducing
seeking delays in P2P VoD applications Examines distributed
optimization techniques for unicast and multicast video streaming
over wireless ad hoc networks Considers the network lifetime
maximization problem in wireless visual sensor networks Detailing
methods that can immediately improve the performance of your video
communication systems, this book presents multiple applications of
optimal resource allocation. For each of the applications,
Visual Question Answering (VQA) usually combines visual inputs like
image and video with a natural language question concerning the
input and generates a natural language answer as the output. This
is by nature a multi-disciplinary research problem, involving
computer vision (CV), natural language processing (NLP), knowledge
representation and reasoning (KR), etc. Further, VQA is an
ambitious undertaking, as it must overcome the challenges of
general image understanding and the question-answering task, as
well as the difficulties entailed by using large-scale databases
with mixed-quality inputs. However, with the advent of deep
learning (DL) and driven by the existence of advanced techniques in
both CV and NLP and the availability of relevant large-scale
datasets, we have recently seen enormous strides in VQA, with more
systems and promising results emerging. This book provides a
comprehensive overview of VQA, covering fundamental theories,
models, datasets, and promising future directions. Given its scope,
it can be used as a textbook on computer vision and natural
language processing, especially for researchers and students in the
area of visual question answering. It also highlights the key
models used in VQA.
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Social Informatics - 7th International Conference, SocInfo 2015, Beijing, China, December 9-12, 2015, Proceedings (Paperback, 1st ed. 2015)
Tie-Yan Liu, Christie Napa Scollon, Wenwu Zhu
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R2,442
Discovery Miles 24 420
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Ships in 10 - 15 working days
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This book constitutes the proceedings of the 7th International
Conference on Social Informatics, SocInfo 2015, held in Beijing,
China, in December 2015. The 19 papers presented in this volume
were carefully reviewed and selected from 42 submissions. They
cover topics such as user modeling, opinion mining, user behavior,
and crowd sourcing.
While most books on the subject focus on resource allocation in
just one type of network, this book is the first to examine the
common characteristics of multiple distributed video communication
systems. Comprehensive and systematic, Optimal Resource Allocation
for Distributed Video Communication presents a unified optimization
framework for resource allocation across these systems. The book
examines the techniques required for optimal resource allocation
over Internet, wireless cellular networks, wireless ad hoc
networks, and wireless sensor networks. It provides you with the
required foundation in video communications, including Peer-to-Peer
(P2P) networks, wireless networks, and visual sensor networks.
Whether you're in industry or academia, you'll value how the book
outlines current challenges facing the field and outlines a general
solution framework for addressing these challenges. From problem
formulations and theoretical analysis to practical algorithms, it
facilitates the comprehensive understanding required to achieve
optimized video and multimedia communications. Presents the
resource allocation techniques for scalable video communications
over Internet or wireless networks Examines two resource allocation
problems-distributed throughput maximization for scalable P2P
Video-on-Demand (VoD) systems and streaming capacity for P2P VoD
systems Outlines an optimal prefetching framework for reducing
seeking delays in P2P VoD applications Examines distributed
optimization techniques for unicast and multicast video streaming
over wireless ad hoc networks Considers the network lifetime
maximization problem in wireless visual sensor networks Detailing
methods that can immediately improve the performance of your video
communication systems, this book presents multiple applications of
optimal resource allocation. For each of the applications,
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