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With the highly increasing availability of text data on the Internet, the process of selecting an appropriate set of features for text classification becomes more important, for not only reducing the dimensionality of the feature space, but also for improving the classification performance. This paper proposes a novel feature selection approach to improve the performance of text classifier based on...
This paper describes a method of training an artificial neural network, specifically a multilayer perceptron (MLP), to act as a tool to help identify plants using morphological characters collected automatically from images of botanical herbarium specimens. A methodology is presented here to provide a practical way for taxonomists to use neural networks as automated identification tools, by collating...
This paper presents methods and principles for knowledge elicitation and semantics definitions for images and text, respectively, and furthermore introduces a semantic representation scheme that fuses the semantic information extracted from image and text to facilitate intelligent indexing and retrieval for multimedia collection as well as media transformation through their semantic meanings. The...
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