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Usually, most of the data generated in real-world such as images, speech signals, or fMRI scans has a high dimensionality. Therefore, dimensionality reduction techniques can be used to reduce the number of variables in that data and then the system performance can be improved. Because the processing of the high dimensional data leads the increase of complexity both in execution time and memory usage...
Handwriting has been known to be a very strong identifying characteristic of an individual and can be considered a behavioural biometric trait. This has made hand writer identification an important area of research. In this paper, a novel offline writer identification system is proposed using ensemble of multi-scale local ternary pattern histogram features. Features are extracted at multiple scales...
The introduction of multispectral imaging in pathology problems such as the identification of prostatic cancer is recent. Unlike conventional RGB color space, it allows the acquisition of a large number of spectral bands within the visible spectrum. This results in a feature vector of size greater than 100. For such a high dimensionality, pattern recognition techniques suffer from the well-known curse...
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