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Other studies have shown the number of satellites used in the location determination and the number of satellites in view can be used to improve classifications of GPS data [ 51].
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Feature combinations can improve classification results [9].
Therefore, we can effectively improve classification efficiency using feature selection.
Many features [5] have been developed to improve classification accuracy.
All those spectral-spatial classifications significantly improve classification results and can be used in succession.
Some form of feature selection will improve classification results and improve the efficiency of the system.
It is well known that a combination of many different classifiers can improve classification accuracy.
In some cases, it can even improve classification accuracy by removing misleading noise.
Naturally, one can expect to improve classification accuracy by augmenting Feature 1 to the raw data.
However, combining texture descriptors to improve classification accuracy is not within the scope of this article.
Support vector machine (SVM) may improve classification result instead of a simple MLP.
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