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Keynote
Speech
Content-based
browsing of image collections
Gerald
Schaefer, Loughborough University, Loughborough,
U.K.
With the exponential growth
of available digital imagery, effective and
efficient techniques to manage these data are
highly sought after. Clearly, image collections
are only of use if they can be queried, yet
manual annotation to enable such search is
expensive, time consuming and error-prone.
Luckily a lot of research in the last two
decades has focused on techniques to extract
useful data directly from images to facilitate
searching large image repositories. In this
tutorial we will explain the underlying
techniques, highlight some of the challenges to
be overcome, and introduce some recent
approaches that provide interesting and useful
methods of working with image datasets.
Speaker
Biography: 
Gerald
Schaefer gained his BSc. in Computing from the
University of Derby and his PhD in Computer
Vision from the University of East Anglia. He
worked at the Colour & Imaging Institute,
University of Derby (1997-1999), in the School
of Information Systems, University of East
Anglia (2000-2001), in the School of Computing
and Informatics at Nottingham Trent University
(2001-2006), and in the School of Engineering
and Applied Science at Aston University
(2006-2009) before joining the Department of
Computer Science at Loughborough University.
His research interests are mainly in the areas
of colour image analysis, image retrieval,
physics-based vision, medical imaging, and
computational intelligence. He has published
extensively in these areas with a total
publication count exceeding 200. He is a
member of the editorial board of several
international journals, reviews for over 50
journals and served on the programme committee
of about 150 conferences. He has been invited
as plenary speaker to several conferences, is
the organiser of some international workshops
and special sessions at conferences, and the
editor of several books and special journal
issues.
For more details please
visit his web page: http://homepages.lboro.ac.uk/~cogs/
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Keynote Speech
Efficient Joins to Process
Semi-Stream Data
M. Asif Naeem,
Auckland University of Technology,
Auckland,
New Zealand
An
important component of
near-real-time data warehouses is
the near-real-time integration
layer. One important element in
near-real-time data integration is
the join of a continuous input data
stream with a disk-based relation.
For high-throughput streams,
stream-based algorithms, such as
Mesh Join (MESHJOIN), can be used.
However, in MESHJOIN the performance
of the algorithm is inversely
proportional to the size of
disk-based relation. The Index
Nested Loop Join (INLJ) can be set
up so that it processes stream
input, and can deal with
intermittences in the update stream
but it has low throughput. This
paper introduces a robust
stream-based join algorithm called
Hybrid Join (HYBRIDJOIN), which
combines the two approaches. A
theoretical result shows that
HYBRIDJOIN is asymptotically as fast
as the fastest of both algorithms.
The authors present performance
measurements of the implementation.
In experiments using synthetic data
based on a Zipfian distribution,
HYBRIDJOIN performs significantly
better for typical parameters of the
Zipfian distribution, and in general
performs in accordance with the
theoretical model while the other
two algorithms are unacceptably slow
under different settings.
Speaker Biography: 
Dr. Muhammad Asif Naeem is presently
a lecturer in School of Computing and
Mathematical Sciences, Auckland
University of Technology, Auckland,
New Zealand. He received his PhD
degree in Computer Science from The
University of Auckland, New
Zealand. He has been
awarded a best PhD thesis award from
The University of Auckland. In his PhD
research he has designed a number of
novel join algorithms to process
various kinds of stream data
efficiently. These algorithms have
been published worldwide and and
can be used in any kind of data
warehouse to scale up their
performance. Before that Asif has
done his Master¡¯s degree with
distinction in the area of Web
Mining. He has about twelve years
research, industrial and teaching
experience. He has published his
research work in high repute
journals, conferences, and workshops
including IEEE, ACM, and VLDB. He
has been reviewing for well-known
journals and conferences in his
area. He is an active IEEE member.
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