Sentence examples for better feature extraction from inspiring English sources

Filtering techniques are used to improve the signal to noise ratio (SNR) for better feature extraction.

These more accurate models can lead to better source localisation as well as to better feature extraction and, consequently, more successful seizure detection.

While better feature extraction and weighting at the isolated word level may improve results, we suspect that significantly better results will require an approach based on natural language understanding.

Its performance is then evaluated by EEG signal classification to show if the proposed approach performed better than other feature extraction methods in classification accuracy.

Additionally, the specificity of the behaviour of certain categories and product ranges determines the need to establish suitable and specific procedures for a better prediction and feature extraction.

subject to {y}_jleft({omega}^Tvarphi left({x}_iright)+bright ge 1-{xi}_j (13) xi ge 0,j=1,2,dots, N. In order to better understand the feature extraction algorithm of this paper, we give the training steps of the network as follows: In this paper, we used the ROC (receiver operating characteristic) curve to estimate the performance of the classification algorithm more comprehensively.

The Gabor wavelet is incorporated with scale-invariant feature transformation (SIFT) for feature extraction to better extract the iris features.

We tried two strategies: (i) dense extract patches from the image on a grid using different sizes and scales and (ii) sparse extract SURF features from the image, since it has been empirically shown to have better results than other feature extraction methods on DR detection [6].

Experiments performed on renowned datasets revealed better performances in terms of feature extraction in robust conditions.

Hence, face recognition is an ongoing area of research, wherein better methods for image representation, feature extraction, and classification are still being sought.

As a method of data preprocessing of the learning algorithm, feature extraction can better improve the accuracy of learning algorithm and shorten the time.