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There is an increasing interest in understanding learning and knowledge development when visitors attend informal institutions, such as museums, science centers, aquariums and botanical gardens. But in what ways do visitors develop new knowledge, skills and awareness about displayed issues in these kinds of settings and how does the exhibition environment affect and scaffold learning processes? In this book, the authors turn their attention to visitors’ and staff members’ actions and dialogues during the visits in order to identify and study learning situations. A common approach is the use and development of socio-cultural and cultural-historical frameworks and theories as means for coming closer to the significance of interactions at different levels and in different contexts. The individual chapters cover learning interactions in relation to staff members’ roles and identities, family visits, exhibitions as resources for professional development and school visits.
Didactics --- didactiek --- Museum exhibits. --- Museum visitors. --- Museums --- Visitors to museums --- Persons --- Museum attendance --- Display techniques --- Displays, Museum --- Museum displays --- Exhibitions --- Museum techniques --- Visitors --- Science museums --- Educational aspects. --- Sociological aspects. --- Science --- Science centers --- Education --- History
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Humans perceive the three-dimensional structure of the world with apparent ease. However, despite all of the recent advances in computer vision research, the dream of having a computer interpret an image at the same level as a two-year old remains elusive. Why is computer vision such a challenging problem and what is the current state of the art? Computer Vision: Algorithms and Applications explores the variety of techniques commonly used to analyze and interpret images. It also describes challenging real-world applications where vision is being successfully used, both for specialized applications such as medical imaging, and for fun, consumer-level tasks such as image editing and stitching, which students can apply to their own personal photos and videos. More than just a source of recipes, this exceptionally authoritative and comprehensive textbook/reference also takes a scientific approach to basic vision problems, formulating physical models of the imaging process before inverting them to produce descriptions of a scene. These problems are also analyzed using statistical models and solved using rigorous engineering techniques Topics and features: Structured to support active curricula and project-oriented courses, with tips in the Introduction for using the book in a variety of customized courses Presents exercises at the end of each chapter with a heavy emphasis on testing algorithms and containing numerous suggestions for small mid-term projects Provides additional material and more detailed mathematical topics in the Appendices, which cover linear algebra, numerical techniques, and Bayesian estimation theory Suggests additional reading at the end of each chapter, including the latest research in each sub-field, in addition to a full Bibliography at the end of the book Supplies supplementary course material for students at the associated website, http://szeliski.org/Book/ Suitable for an upper-level undergraduate or graduate-level course in computer science or engineering, this textbook focuses on basic techniques that work under real-world conditions and encourages students to push their creative boundaries. Its design and exposition also make it eminently suitable as a unique reference to the fundamental techniques and current research literature in computer vision. Dr. Richard Szeliski has more than 25 years' experience in computer vision research, most notably at Digital Equipment Corporation and Microsoft Research. This text draws on that experience, as well as on computer vision courses he has taught at the University of Washington and Stanford.
Computer. Automation --- beeldverwerking --- Computer vision --- Image processing --- Computer algorithms --- Bildverarbeitung. --- Computer algorithms. --- Computer vision. --- Image processing. --- Maschinelles Sehen. --- Image Processing and Computer Vision. --- Vision par ordinateur. --- 681.3*I41 --- 681.3*I4 --- 681.3*I5 --- Pictorial data processing --- Picture processing --- Processing, Image --- Imaging systems --- Optical data processing --- Machine vision --- Vision, Computer --- Artificial intelligence --- Pattern recognition systems --- Algorithms --- 681.3*I5 Pattern recognition (Computing methodologies) --- Pattern recognition (Computing methodologies) --- 681.3*I41 Digitization; quantization; sampling; scanning (Image processing) --- Digitization; quantization; sampling; scanning (Image processing) --- 681.3*I4 Image processing: image displays; image processing software (Computing methododologies) --- Image processing: image displays; image processing software (Computing methododologies) --- Optical data processing. --- Optical computing --- Visual data processing --- Bionics --- Electronic data processing --- Integrated optics --- Photonics --- Computers --- Optical equipment --- Mathematics.
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