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Later, we will look into the conventional features employed in emotion detection and will discuss the associated problems.
The MPEG7 descriptors can be interpreted as a compromised feature set between the conventional features and the perceptual features.
Thus, the inclusion of spectro-temporal information was considered relevant to complement the conventional features and to support classification.
With the STFT-ranking feature, the recognition performance (93.9%) is superior to the conventional features (33.3 90.8%).
It is concluded from the related study that the conventional features have a robust performance in arousal dimension rather than the valence domain.
Since the conventional features are originally proposed for speech recognition, they may not fully model the emotion perception of the human ear [10, 11].
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The KFA-based virtual sensing model outperforms the conventional feature selection based virtual sensing models.
The results show that the proposed framework is more robust against blurring than the conventional feature- and appearance-based methods.
The performance of the hybrid models were compared to those of the individual models without the non-linear but with the conventional feature selection algorithm.
The effectiveness of the presented virtual sensing method is validated in the experimental studies of gear wear, and the comparison results show that the presented KFA scheme outperforms the conventional feature selection techniques in terms of virtual sensing model accuracy.
Some of the recent approaches that attempt to improve the performance of the conventional feature selection methods use the ideas of neighborhood margins [44 46], and manifold regularization using SVMs [47].
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com