Learning and Recognizing Visual Object Categories

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Over the past few years there has been substantial progress in the development of techniques for recognizing generic categories of objects in images, such as automobiles, bicycles, airplanes, and human faces. Much of this progress can be traced to two underlying technical advances: (i) detectors for locally invariant features of an image, and (ii) the application of techniques from machine learning. Despite recent successes, however, there are some fundamental concerns about methods that rely heavily on feature detection, because the local image evidence used in detection decisions is often highly ambiguous due to the absence of contextual information.

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google
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learning
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