Semi-supervised classification uses aspects of both unsupervised and supervised learning to improve upon the performance of traditional classification methods. Semi-supervised clu...
The discovery of frequently occurring patterns in a time series could be important in several application contexts. As an example, the analysis of frequent patterns in biomedical ...
Classification with only one labeled example per class is a challenging problem in machine learning and pattern recognition. While there have been some attempts to address this pr...
Feature extraction and classification are two important components in pattern recognition. In this paper, we propose dynamic target classification in WSNs. The main idea of this a...
The description of the object shape is an important characteristic of the image. In image processing and pattern recognition, several different shape descriptors are used. In huma...