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A charming evocation of life in Beijing in the 1940s and 50s for a
small child growing through the enormous social change in China at
that time. Little Auspicious and his family experience
unforgettable adventures involving secret agents, spies, Japanese
invaders, the Kuomintang and dangerous encounters and escapades
before Beijing is liberated and New China is created. An accessible
and beautifully illustrated narrative of life in Beijing at a time
of immense change this book will appeal to teenagers and all who
wish to learn more about China during this period.
This is the first book illustrating China's forest carbon projects.
It includes an analysis of the policy and future development trends
of China's forest carbon market and showcases the country's most
representative forest carbon projects. Accordingly, it offers a
valuable resource for all policymakers and researchers interested
in forest carbon, as well as project developers and engineers
involved in forest carbon projects.
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Deep Learning and Data Labeling for Medical Applications - First International Workshop, LABELS 2016, and Second International Workshop, DLMIA 2016, Held in Conjunction with MICCAI 2016, Athens, Greece, October 21, 2016, Proceedings (Paperback, 1st ed. 2016)
Gustavo Carneiro, Diana Mateus, Loic Peter, Andrew Bradley, Joao Manuel R.S. Tavares, …
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R2,418
Discovery Miles 24 180
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Ships in 10 - 15 working days
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This book constitutes the refereed proceedings of two workshops
held at the 19th International Conference on Medical Image
Computing and Computer-Assisted Intervention, MICCAI 2016, in
Athens, Greece, in October 2016: the First Workshop on Large-Scale
Annotation of Biomedical Data and Expert Label Synthesis, LABELS
2016, and the Second International Workshop on Deep Learning in
Medical Image Analysis, DLMIA 2016. The 28 revised regular papers
presented in this book were carefully reviewed and selected from a
total of 52 submissions. The 7 papers selected for LABELS deal with
topics from the following fields: crowd-sourcing methods; active
learning; transfer learning; semi-supervised learning; and modeling
of label uncertainty.The 21 papers selected for DLMIA span a wide
range of topics such as image description; medical imaging-based
diagnosis; medical signal-based diagnosis; medical image
reconstruction and model selection using deep learning techniques;
meta-heuristic techniques for fine-tuning parameter in deep
learning-based architectures; and applications based on deep
learning techniques.
This volume consists of introductory lectures on the topics in the
new and rapidly developing area of toric homotopy theory, and its
applications to the current research in configuration spaces and
braids, as well as to more applicable mathematics such as fr-codes
and robot motion planning.The book starts intertwining homotopy
theoretical and combinatorial ideas within the remits of toric
topology and illustrates an attempt to classify in a combinatorial
way polytopes known as fullerenes, which are important objects in
quantum physics, quantum chemistry and nanotechnology. Toric
homotopy theory is then introduced as a further development of
toric topology, which describes properties of Davis-Januszkiewicz
spaces, moment-angle complexes and their generalizations to
polyhedral products. The book also displays the current research on
configuration spaces, braids, the theory of limits over the
category of presentations and the theory of fr-codes. As an
application to robotics, the book surveys topological problems
relevant to the motion planning problem of robotics and includes
new results and constructions, which enrich the emerging area of
topological robotics.The book is at research entry level addressing
the core components in homotopy theory and their important
applications in the sciences and thus suitable for advanced
undergraduate and graduate students.
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