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Sloan’s Lake had a long history of entertaining Denver residents
with boating, fishing, swimming, and a steamboat canal built in the
1870s. In 1890, Adam Graff and his partners opened a new park on
the shore of Sloan’s Lake that would eventually become Manhattan
Beach. Originally created as a summer pleasure resort with a highly
respected summer theater, boating, fishing, and music, the park
quickly expanded to include typical amusement attractions,
including Denver’s first roller coaster and merry-go-round. When
the concept of the amusement park was created in 1895 with the
opening of Sea Lion Park on Coney Island in New York, Manhattan
Beach was already a step ahead of rivals Elitch Gardens and
Arlington Park. Operating from 1890 to 1914, Manhattan Beach
Amusement Park was the first true amusement park in Denver and was
enjoyed by residents and visitors for nearly twenty-five years as
Denver tried to shake off its image as a dusty cow town from gold
mining days and fought to be seen as a sophisticated and
well-developed city. Manhattan Beach played an important role in
amusement park history in the United States, but its full story has
never before been told. Manhattan Beach’s story is an important
addition to both Denver and Colorado’s history as it reflects the
city’s growth during the late 1800s and early 1900s. The park has
also inspired many legends, the most famous of which concerns Roger
the Elephant, who arrived at Manhattan Beach in 1891, and his
supposed death and burial in a swamp near the park. Much of what
has been told about Manhattan Beach in the years since it closed is
more myth than fact, as this book demonstrates. After the amusement
park closed in 1914, the city of Denver purchased the land and
turned it into Sloan’s Lake Park, which continues to be a
gathering place for Denverites.
Appropriate for upper-division undergraduate- and graduate-level
courses in computer vision found in departments of Computer
Science, Computer Engineering and Electrical Engineering. This
textbook provides the most complete treatment of modern computer
vision methods by two of the leading authorities in the field. This
accessible presentation gives both a general view of the entire
computer vision enterprise and also offers sufficient detail for
students to be able to build useful applications. Students will
learn techniques that have proven to be useful by first-hand
experience and a wide range of mathematical methods.
Machine learning methods are now an important tool for scientists,
researchers, engineers and students in a wide range of areas. This
book is written for people who want to adopt and use the main tools
of machine learning, but aren't necessarily going to want to be
machine learning researchers. Intended for students in final year
undergraduate or first year graduate computer science programs in
machine learning, this textbook is a machine learning toolkit.
Applied Machine Learning covers many topics for people who want to
use machine learning processes to get things done, with a strong
emphasis on using existing tools and packages, rather than writing
one's own code. A companion to the author's Probability and
Statistics for Computer Science, this book picks up where the
earlier book left off (but also supplies a summary of probability
that the reader can use). Emphasizing the usefulness of standard
machinery from applied statistics, this textbook gives an overview
of the major applied areas in learning, including coverage of:*
classification using standard machinery (naive bayes; nearest
neighbor; SVM)* clustering and vector quantization (largely as in
PSCS)* PCA (largely as in PSCS)* variants of PCA (NIPALS; latent
semantic analysis; canonical correlation analysis)* linear
regression (largely as in PSCS)* generalized linear models
including logistic regression* model selection with Lasso,
elasticnet* robustness and m-estimators* Markov chains and HMM's
(largely as in PSCS)* EM in fairly gory detail; long experience
teaching this suggests one detailed example is required, which
students hate; but once they've been through that, the next one is
easy* simple graphical models (in the variational inference
section)* classification with neural networks, with a particular
emphasis onimage classification* autoencoding with neural networks*
structure learning
In 1914, as the world prepared for war, thousands of men enlisted
in Scotland. But thousands more Scots, and those of Scottish
descent, joined up across the world. As the optimism of 1914 gave
way to the grim reality of years of conflict, the human cost of
fighting the First World War became a foundation of national
consciousness - for Canada at Vimy Ridge, for Australia and New
Zealand at Gallipoli, for South Africa at Delville Wood. Based on
the exhibition at the National Museum of Scotland (11 July to 12
October 2014) the book explores how military service was related to
other expressions of Scottish identity. And, following the
structure of the exhibition, personal story vignettes, based on
National Museum Scotland and on international collections, will
reinforce the main themes of migration, multiple identity and loss.
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Computer Vision - ECCV 2008 - 10th European Conference on Computer Vision, Marseille, France, October 12-18, 2008, Proceedings, Part I (Paperback, 2008 ed.)
David Forsyth, Philip Torr, Andrew Zisserman
|
R2,948
Discovery Miles 29 480
|
Ships in 10 - 15 working days
|
Welcome to the 2008EuropeanConference onComputer Vision. These
proce- ings are the result of a great deal of hard work by many
people. To produce them, a total of 871 papers were reviewed. Forty
were selected for oral pres- tation and 203 were selected for
poster presentation, yielding acceptance rates of 4.6% for oral,
23.3% for poster, and 27.9% in total.
Weappliedthreeprinciples.First, sincewehadastronggroupofAreaChairs,
the ?nal decisions to accept or reject a paper rested with the Area
Chair, who
wouldbeinformedbyreviewsandcouldactonlyinconsensuswithanotherArea
Chair. Second, we felt that authors were entitled to a summary that
explained how the Area Chair reached a decision for a paper. Third,
we were very careful to avoid con?icts of interest. Each paper was
assigned to an Area Chair by the Program Chairs, and each Area
Chair received a pool of about 25 papers. The Area Chairs then
identi?ed and rankedappropriatereviewersfor eachpaper in their
pool, and a constrained optimization allocated three reviewers to
each paper. We are very proud that every paper received at least
three reviews. At this point, authors were able to respond to
reviews. The Area Chairs then needed to reach a decision. We used a
series of procedures to ensure careful review and to avoid con?icts
of interest. ProgramChairs did not submit papers. The Area Chairs
were divided into three groups so that no Area Chair in the group
was in con?ict with any paper assigned to any Area Chair in the
group
|
Computer Vision - ECCV 2008 - 10th European Conference on Computer Vision, Marseille, France, October 12-18, 2008, Proceedings, Part IV (Paperback, 2008 ed.)
David Forsyth, Philip Torr, Andrew Zisserman
|
R2,970
Discovery Miles 29 700
|
Ships in 10 - 15 working days
|
Welcome to the 2008EuropeanConference onComputer Vision. These
proce- ings are the result of a great deal of hard work by many
people. To produce them, a total of 871 papers were reviewed. Forty
were selected for oral pres- tation and 203 were selected for
poster presentation, yielding acceptance rates of 4.6% for oral,
23.3% for poster, and 27.9% in total.
Weappliedthreeprinciples.First, sincewehadastronggroupofAreaChairs,
the ?nal decisions to accept or reject a paper rested with the Area
Chair, who
wouldbeinformedbyreviewsandcouldactonlyinconsensuswithanotherArea
Chair. Second, we felt that authors were entitled to a summary that
explained how the Area Chair reached a decision for a paper. Third,
we were very careful to avoid con?icts of interest. Each paper was
assigned to an Area Chair by the Program Chairs, and each Area
Chair received a pool of about 25 papers. The Area Chairs then
identi?ed and rankedappropriatereviewersfor eachpaper in their
pool, and a constrained optimization allocated three reviewers to
each paper. We are very proud that every paper received at least
three reviews. At this point, authors were able to respond to
reviews. The Area Chairs then needed to reach a decision. We used a
series of procedures to ensure careful review and to avoid con?icts
of interest. ProgramChairs did not submit papers. The Area Chairs
were divided into three groups so that no Area Chair in the group
was in con?ict with any paper assigned to any Area Chair in the
group
Welcome to the 2008EuropeanConference onComputer Vision. These
proce- ings are the result of a great deal of hard work by many
people. To produce them, a total of 871 papers were reviewed. Forty
were selected for oral pres- tation and 203 were selected for
poster presentation, yielding acceptance rates of 4.6% for oral,
23.3% for poster, and 27.9% in total.
Weappliedthreeprinciples.First, sincewehadastronggroupofAreaChairs,
the ?nal decisions to accept or reject a paper rested with the Area
Chair, who
wouldbeinformedbyreviewsandcouldactonlyinconsensuswithanotherArea
Chair. Second, we felt that authors were entitled to a summary that
explained how the Area Chair reached a decision for a paper. Third,
we were very careful to avoid con?icts of interest. Each paper was
assigned to an Area Chair by the Program Chairs, and each Area
Chair received a pool of about 25 papers. The Area Chairs then
identi?ed and rankedappropriatereviewersfor eachpaper in their
pool, and a constrained optimization allocated three reviewers to
each paper. We are very proud that every paper received at least
three reviews. At this point, authors wereable to respond to
reviews. The Area Chairs then needed to reach a decision. We used a
series of procedures to ensure careful review and to avoid con?icts
of interest. ProgramChairs did not submit papers. The Area Chairs
were divided into three groups so that no Area Chair in the group
was in con?ict with any paper assigned to any Area Chair in the
group
|
Computer Vision - ECCV 2008 - 10th European Conference on Computer Vision, Marseille, France, October 12-18, 2008, Proceedings, Part III (Paperback, 2008 ed.)
David Forsyth, Philip Torr, Andrew Zisserman
|
R2,950
Discovery Miles 29 500
|
Ships in 10 - 15 working days
|
Welcome to the 2008EuropeanConference onComputer Vision. These
proce- ings are the result of a great deal of hard work by many
people. To produce them, a total of 871 papers were reviewed. Forty
were selected for oral pres- tation and 203 were selected for
poster presentation, yielding acceptance rates of 4.6% for oral,
23.3% for poster, and 27.9% in total.
Weappliedthreeprinciples.First, sincewehadastronggroupofAreaChairs,
the ?nal decisions to accept or reject a paper rested with the Area
Chair, who
wouldbeinformedbyreviewsandcouldactonlyinconsensuswithanotherArea
Chair. Second, we felt that authors were entitled to a summary that
explained how the Area Chair reached a decision for a paper. Third,
we were very careful to avoid con?icts of interest. Each paper was
assigned to an Area Chair by the Program Chairs, and each Area
Chair received a pool of about 25 papers. The Area Chairs then
identi?ed and rankedappropriatereviewersfor eachpaper in their
pool, and a constrained optimization allocated three reviewers to
each paper. We are very proud that every paper received at least
three reviews. At this point, authors were able to respond to
reviews. The Area Chairs then needed to reach a decision. We used a
series of procedures to ensure careful review and to avoid con?icts
of interest. ProgramChairs did not submit papers. The Area Chairs
were divided into three groups so that no Area Chair in the group
was in con?ict with any paper assigned to any Area Chair in the
group
This book is the proceedings of the Second Joint European-US
Workshop on Applications of Invariance to Computer Vision, held at
Ponta Delgada, Azores, Portugal in October 1993.
The book contains 25 carefully refereed papers by distinguished
researchers. The papers cover all relevant foundational aspects of
geometric and algebraic invariance as well as applications to
computer vision, particularly to recovery and reconstruction,
object recognition, scene analysis, robotic navigation, and
statistical analysis. In total, the collection of papers, together
with an introductory survey by the editors, impressively documents
that geometry, in its different variants, is the most successful
and ubiquitous tool in computer vision.
This textbook is aimed at computer science undergraduates late in
sophomore or early in junior year, supplying a comprehensive
background in qualitative and quantitative data analysis,
probability, random variables, and statistical methods, including
machine learning. With careful treatment of topics that fill the
curricular needs for the course, Probability and Statistics for
Computer Science features: * A treatment of random variables and
expectations dealing primarily with the discrete case. * A
practical treatment of simulation, showing how many interesting
probabilities and expectations can be extracted, with particular
emphasis on Markov chains. * A clear but crisp account of simple
point inference strategies (maximum likelihood; Bayesian inference)
in simple contexts. This is extended to cover some confidence
intervals, samples and populations for random sampling with
replacement, and the simplest hypothesis testing. * A chapter
dealing with classification, explaining why it's useful; how to
train SVM classifiers with stochastic gradient descent; and how to
use implementations of more advanced methods such as random forests
and nearest neighbors. * A chapter dealing with regression,
explaining how to set up, use and understand linear regression and
nearest neighbors regression in practical problems. * A chapter
dealing with principal components analysis, developing intuition
carefully, and including numerous practical examples. There is a
brief description of multivariate scaling via principal coordinate
analysis. * A chapter dealing with clustering via agglomerative
methods and k-means, showing how to build vector quantized features
for complex signals. Illustrated throughout, each main chapter
includes many worked examples and other pedagogical elements such
as boxed Procedures, Definitions, Useful Facts, and Remember This
(short tips). Problems and Programming Exercises are at the end of
each chapter, with a summary of what the reader should know.
Instructor resources include a full set of model solutions for all
problems, and an Instructor's Manual with accompanying presentation
slides.
Broad beliefs about the economics of 'developing countries' and of
the development process have changed considerably since the subject
became of wide interest in the 1950s; due largely to changes in the
world and in the application of economic policies within developing
countries. Subjects such as environment, gender, poverty, famine
and globalization have come to be of increasingly important public
interest. The extreme divergence of experience among regions of the
world has also made it more and more questionable whether it even
makes sense to think of a single and distinctive 'economics of
developing countries'. This textbook presents a concise and
up-to-date examination of the field of development economics,
bringing together historical perspectives, current issues and
policy implications. Each chapter can be read as a stand-alone
unit, or as part of the wider economic debates presented throughout
the book.
This scarce antiquarian book is a selection from Kessinger
PublishingA AcentsAcentsa A-Acentsa Acentss Legacy Reprint Series.
Due to its age, it may contain imperfections such as marks,
notations, marginalia and flawed pages. Because we believe this
work is culturally important, we have made it available as part of
our commitment to protecting, preserving, and promoting the world's
literature. Kessinger Publishing is the place to find hundreds of
thousands of rare and hard-to-find books with something of intere
Human rights is all too often the first casualty of national
insecurity. How can democracies cope with the threat of terror
while protecting human rights? This timely volume compares the
lessons of the United States and Israel with the "best-case
scenarios" of the United Kingdom, Canada, Spain, and Germany. It
demonstrates that threatened democracies have important options,
and democratic governance, the rule of law, and international
cooperation are crucial foundations for counterterror policy. The
contributors include: Howard Adelman, Colm Campbell, Pilar Domingo,
Richard Falk, David Forsythe, Wolfgang S. Heinz, Pedro Ibarra, Todd
Landman, Salvador Marti, and, Daniel Wehrenfennig.
Machine learning methods are now an important tool for scientists,
researchers, engineers and students in a wide range of areas. This
book is written for people who want to adopt and use the main tools
of machine learning, but aren't necessarily going to want to be
machine learning researchers. Intended for students in final year
undergraduate or first year graduate computer science programs in
machine learning, this textbook is a machine learning toolkit.
Applied Machine Learning covers many topics for people who want to
use machine learning processes to get things done, with a strong
emphasis on using existing tools and packages, rather than writing
one's own code. A companion to the author's Probability and
Statistics for Computer Science, this book picks up where the
earlier book left off (but also supplies a summary of probability
that the reader can use). Emphasizing the usefulness of standard
machinery from applied statistics, this textbook gives an overview
of the major applied areas in learning, including coverage of:*
classification using standard machinery (naive bayes; nearest
neighbor; SVM)* clustering and vector quantization (largely as in
PSCS)* PCA (largely as in PSCS)* variants of PCA (NIPALS; latent
semantic analysis; canonical correlation analysis)* linear
regression (largely as in PSCS)* generalized linear models
including logistic regression* model selection with Lasso,
elasticnet* robustness and m-estimators* Markov chains and HMM's
(largely as in PSCS)* EM in fairly gory detail; long experience
teaching this suggests one detailed example is required, which
students hate; but once they've been through that, the next one is
easy* simple graphical models (in the variational inference
section)* classification with neural networks, with a particular
emphasis onimage classification* autoencoding with neural networks*
structure learning
This volume emerged from an international research colloquium
jointly organised by National Museums Scotland and the Scottish
Centre for Diaspora Studies, University of Edinburgh, funded by the
Scottish Government and administered by the Royal Society of
Edinburgh. Historians and museum curators from Australia, Canada,
New Zealand and South Africa were invited to join with their
Scottish counterparts to consider the functioning, and the meaning,
of 'military Scottishness' in different Commonwealth countries and
in Britain from the late Victorian period to the present day, with
a particular focus on the impact of the First World War. Another
key objective was to throw light on the 'hidden' culture of social
networking which potentially operated behind local regiments and
military units amongst Scotland's global diaspora. This edited
collection provides a comparative overview of the nineteenth
century emergence of military Scottishness and explores how the
construction and performance of Scottish military identity has
evolved in different Commonwealth countries over the late
nineteenth and twentieth centuries. In particular, it looks at the
ways in which Scottish volunteer regiments in Commonwealth
countries variously sought to draw upon, align themselves with or,
at certain key moments, redefine the assertions of martial identity
which Highland regiments represented.
This volume emerged from an international research colloquium
jointly organised by National Museums Scotland and the Scottish
Centre for Diaspora Studies, University of Edinburgh, funded by the
Scottish Government and administered by the Royal Society of
Edinburgh. Historians and museum curators from Australia, Canada,
New Zealand and South Africa were invited to join with their
Scottish counterparts to consider the functioning, and the meaning,
of 'military Scottishness' in different Commonwealth countries and
in Britain from the late Victorian period to the present day, with
a particular focus on the impact of the First World War. Another
key objective was to throw light on the 'hidden' culture of social
networking which potentially operated behind local regiments and
military units amongst Scotland's global diaspora. This edited
collection provides a comparative overview of the nineteenth
century emergence of military Scottishness and explores how the
construction and performance of Scottish military identity has
evolved in different Commonwealth countries over the late
nineteenth and twentieth centuries. In particular, it looks at the
ways in which Scottish volunteer regiments in Commonwealth
countries variously sought to draw upon, align themselves with or,
at certain key moments, redefine the assertions of martial identity
which Highland regiments represented.
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