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Abstract: We study the problem of object classification when training and test classes are disjoint, i.e. no training examples of the target classes are available. This setup has hardly been studied ...
Abstract: Recognizing objects directly from optical fiber output images is useful in endoscopic applications when forming a clear image of the object is unnecessary or rather difficult. Conventional ...
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