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One-shot learning is a challenging problem where the aim is to recognize a class identified by a single training image. Given the practical importance of one-shot learning, it seems surprising that the rich information present in the class tag itself has largely been ignored. Most existing approaches restrict the use of the class tag to finding similar classes and transferring classifiers or metrics...
In this paper, we propose a convolutional framework for short texts expansion and classification. Particularly, by using additive composition over word embeddings from context with variable window width, the representations of multi-scale semantic units are computed first. Empirically, the semantically related words are usually close to each other in embedding spaces. Thus, the restricted nearest...
A famous biologically inspired hierarchical model (HMAX model), which was proposed recently and corresponds to V1 to V4 of the ventral pathway in primate visual cortex, has been successfully applied to multiple visual recognition tasks. The model is able to achieve a set of position- and scale-tolerant recognition, which is a central problem in pattern recognition. In this paper, based on some other...
Conference Web pages are the main platforms to share the conference information and organize conference events. To discover the academic knowledge from such Web pages for building academic ontologies or social networks, it is necessary to extract academic information from conference Web pages. This paper proposes an approach to extract academic information from conference Web pages. Firstly, Web pages...
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