Discriminative Transformation for Multi-Dimensional Temporal Sequences
IEEE Transactions on Image Processing(2017)
Abstract
Feature space transformation techniques have been widely studied for dimensionality reduction in vector-based feature space. However, these techniques are inapplicable to sequence data because the features in the same sequence are not independent. In this paper, we propose a method called max-min inter-sequence distance analysis (MMSDA) to transform features in sequences into a low-dimensional sub...
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Key words
Hidden Markov models,Electronic mail,Data models,Transforms,Character recognition,Training,Adaptation models
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