Klosterneuburg, Austria

Computer Vision and Machine Learning

Language: English Studies in English
Subject area: computer science
University website: www.ist.ac.at
Computer
A computer is a device that can be instructed to carry out sequences of arithmetic or logical operations automatically via computer programming. Modern computers have the ability to follow generalized sets of operations, called programs. These programs enable computers to perform an extremely wide range of tasks.
Computer Vision
Computer vision is an interdisciplinary field that deals with how computers can be made for gaining high-level understanding from digital images or videos. From the perspective of engineering, it seeks to automate tasks that the human visual system can do.
Machine
A machine uses power to apply forces and control movement to perform an intended action. Machines can be driven by animals and people, by natural forces such as wind and water, and by chemical, thermal, or electrical power, and include a system of mechanisms that shape the actuator input to achieve a specific application of output forces and movement. They can also include computers and sensors that monitor performance and plan movement, often called mechanical systems.
Machine Learning
Machine learning is a field of computer science that often uses statistical techniques to give computers the ability to "learn" (i.e., progressively improve performance on a specific task) with data, without being explicitly programmed.
Vision
Vision or The Vision may refer to:
Vision
Two men look out through the same bars:
One sees the mud, and one the stars.
Frederick Langbridge, In A Cluster of Quiet Thoughts; published by the Religious Tract Society.
Vision
For sight is woman-like and shuns the old.
(Ah! he can see enough, when years are told,
Who backwards looks).
Victor Hugo, Eviradnus, IX.
Vision
For any man with half an eye,
What stands before him may espy;
But optics sharp it needs I ween,
To see what is not to be seen.
John Trumbull, McFingal (1775-1782), Canto I, line 67.
Understanding how glacier sliding and iceberg calving contribute to loss in ice sheet models can improve predictions of global sea-level changes. This is hampered by the inaccessibility of a glacier's base and its calving front.
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