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Reproducible Research in Pattern Recognition - Second International Workshop, RRPR 2018, Beijing, China, August 20, 2018, Revised Selected Papers (Paperback, 1st ed. 2019)
Bertrand Kerautret, Miguel Colom, Daniel Lopresti, Pascal Monasse, Hugues Talbot
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R1,557
Discovery Miles 15 570
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Ships in 10 - 15 working days
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This book constitutes the thoroughly refereed post-workshop
proceedings of the Second International Workshop on Reproducible
Research in Pattern Recognition, RRPR 2018, in Beijing, China in
August 2018. The 8 revised full papers, presented together 6 short
papers, were carefully reviewed and selected from 14 submissions.
This year the workshop did focus on Digital Geometry and
Mathematical Morphology. The first track 1 on RR Framework was
dedicated to the general topics of Reproducible Research in
Computer Sciencewith a potential link to Image Processing and
Pattern Recognition. In the second track 2 the authors described
their works in terms of Reproducible Research.
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Reproducible Research in Pattern Recognition - 4th ICPR International Workshop, RRPR 2022, Montreal, Canada, August 21, 2022, Revised Selected Papers (1st ed. 2023)
Bertrand Kerautret, Miguel Colom, Adrien Krähenbühl, Daniel Lopresti, Pascal Monasse, …
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R1,568
Discovery Miles 15 680
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Ships in 10 - 15 working days
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This book constitutes the thoroughly refereed post-workshop
proceedings of the 4th International Workshop on Reproducible
Research in Pattern Recognition, RRPR 2022, held in Montreal,
Canada, in August 2022. The 5 revised full papers presented
together with 4 short papers, were carefully reviewed and selected
from 9 submissions. The papers were organized into three main
categories
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Reproducible Research in Pattern Recognition - Third International Workshop, RRPR 2021, Virtual Event, January 11, 2021, Revised Selected Papers (Paperback, 1st ed. 2021)
Bertrand Kerautret, Miguel Colom, Adrien Krahenbuhl, Daniel Lopresti, Pascal Monasse, …
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R1,557
Discovery Miles 15 570
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Ships in 10 - 15 working days
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This book constitutes the thoroughly refereed post-workshop
proceedings of the Third International Workshop on Reproducible
Research in Pattern Recognition, RRPR 2021, held as a virtual
event, in January 2021. The 8 revised full papers, presented
together with 6 short papers, were carefully reviewed and selected
from 18 submissions. The papers were organized into three main
categories. The first contributions focused on reproducible
research frameworks. The second category focused on reproducible
research results and the last category included ICPR companion
papers describing implementation and details that are an absolute
requirement for reproducibility.
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Reproducible Research in Pattern Recognition - First International Workshop, RRPR 2016, Cancun, Mexico, December 4, 2016, Revised Selected Papers (Paperback, 1st ed. 2017)
Bertrand Kerautret, Miguel Colom, Pascal Monasse
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R2,096
Discovery Miles 20 960
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Ships in 10 - 15 working days
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This book constitutes the thoroughly refereed post-proceedings of
the First International Workshop on Reproducible Research in
Pattern Recognition, RRPR 2016, held in Cancun, Mexico, in December
2016. The 12 revised full papers, among them 2 invited talks,
presented were carefully reviewed and selected from 16 submissions.
They focus on pattern recognition algorithms; reproducible research
frameworks; reproducible research results, previous works on
reproducible research.
This book discusses the basic geometric contents of an image and
presents a
treedatastructuretohandleite?ciently.Itanalyzesalsosomemorphological
operators that simplify this geometric contents and their
implementation in termsofthe
datastructuresintroduced.It?nallyreviewsseveralapplications to
image comparison and registration, to edge and corner computation,
and the selection of features associated to a given scale in
images. Let us ?rst say that, to avoid a long list, we shall not
give references in this summary; they are obviously contained in
this monograph. A gray level image is usually modeled as a function
de?ned in a bounded N domain D? R (typically N = 2 for usual
snapshots, N=3formedical images or movies) with values in R. The
sensors of a camera or a CCD array transform the continuum of light
energies to a ?nite interval of values by means of a nonlinear
function g. The contrast change g depends on the pr-
ertiesofthesensors,butalsoontheilluminationconditionsandthere?ection
propertiesofthe
objects,andthoseconditionsaregenerallyunknown.Images are thus
observed modulo an arbitrary and unknown contrast change.
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