منابع مشابه
Watch What I Watch
This paper presents a high-level overview of Yahoo Research Berkeley’s approach to multimedia research and the ideas motivating it. This approach is characterized primarily by a shift away from building subsystems that attempt to discover or understand the “meaning” of media content toward systems and algorithms that can usefully utilize information about how media content is being used in spec...
متن کاملObservational Learning: Tell Beginners What They Are about to Watch and They Will Learn Better
Observation aids motor skill learning. When multiple models or different levels of performance are observed, does learning improve when the observer is informed of the performance quality prior to each observation trial or after each trial? We used a knock-down barrier task and asked participants to learn a new relative timing pattern that differed from that naturally emerging from the task con...
متن کاملWatch and Learn: Seeing Is Better than Doing when Acquiring Consecutive Motor Tasks
During motor adaptation learning, consecutive physical practice of two different tasks compromises the retention of the first. However, there is evidence that observational practice, while still effectively aiding acquisition, will not lead to interference and hence prove to be a better practice method. Observers and Actors practised in a clockwise (Task A) followed by a counterclockwise (Task ...
متن کامل"I don't watch TV to like learn anything": The Leisure Use of TV and the Internet
This paper is an analysis of how Norwegians use television and the Internet in their leisure time. It sets up a taxonomy using the degree of engagement in the mediated information on one axis and the degree of sociability on the other. Within this matrix one can examine the similarities and differences between the two media and also differences between the generations. The analysis is based on ...
متن کاملWatch and Learn: Semi-Supervised Learning for Object Detectors From Video
We present a semi-supervised approach that localizes multiple unknown object instances in long videos. We start with a handful of labeled boxes and iteratively learn and label hundreds of thousands of object instances. We propose criteria for reliable object detection and tracking for constraining the semi-supervised learning process and minimizing semantic drift. Our approach does not assume e...
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ژورنال
عنوان ژورنال: Nature Reviews Molecular Cell Biology
سال: 2007
ISSN: 1471-0072,1471-0080
DOI: 10.1038/nrm2097