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Learning and vision machines
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DOI：10.1109/JPROC.2002.801450.png)
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摘要
En 中文
The problem of learning is arguably at the very core of the Problem of intelligence, both biological and artificial. In this paper, we review our approach to the problem of visual perception based on supervised learning. After a brief presentation of the theoretical background, we focus on some of the engineering applications of statistical learning to computer vision and discuss the main open problems and directions of our future research.
Keyword:
morphable models
object categorization
object detection
object recognition
pattern classification
support vector machines
visual learning
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