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Different researches show that in solving the pattern classification problems the LDA-based algorithms outperform the PCA-based ones, since the former take the between classes variations into account.
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Because of the generality and importance of these gene classes, variation in their function is expected to affect a variety of cellular mechanisms, complicating their possible functional relationship to Fusarium ear rot resistance.
Based on the learned representations through multiple hidden layers, a representation clustering algorithm is proposed to minimize the distance of intra-class variations and maximize the distance of inter-class variations simultaneously.
An individual-specific ensemble of exemplar-SVM (e-SVM) classifiers is thereby designed to improve robustness to intra-class variations.
Iris images acquired in heterogeneous environment have large intra-class variations, such as different resolutions or different sensor optics, etc.
Semantic image segmentation is challenging due to the large intra-class variations and the complex spatial layouts inside natural scenes.
This task is normally difficult due to complex data in the form of heterogeneous appearance with large intra-class and lower inter-class variations.
In addition, along with the rapid growth in the data volume, new classification methodology is also demanded to explicitly handle the intra-class variations.
Therefore, it is challenging to manually design a robust encoding filter to face the complex intra-class variations of heterogeneous iris images.
Unfortunately, error rate values estimated during the system design are subject to variations due to several aspects: intra-class variations arising on small-medium time-window, and ageing, which is the natural process involving any biometrics.
In addition to the classical recognition challenges, the food recognition problem is characterized by the absence of a rigid structure of the food and by large intra-class variations.
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