This paper focuses on performance robustness in the sense that the extracted features are desired to be largely insensitive to environmental uncertainties, ...

This paper focuses on performance robustness in the sense that the extracted features are desired to be largely insensitive to environmental uncertainties, ...

Dive into the research topics of 'Performance robustness of feature extraction for target detection & classification'. Together they form a unique fingerprint.

This paper addresses the problem of target detection and classification, where the performance is often limited due to high rates of false alarm and ...

This paper addresses sensor network-based surveillance of target detection and target type & motion classification by investigating a feature extraction ...

These feature extraction techniques were applied on pre-processed frames to extract the efficient features from multi-scale images. Finally, the features are ...

We show that the performance of this method is on par with the state of the art, as the classification accuracy is close to 86% with 7 classes for AIS data, and ...

The results show consistently superior performance of SDF-based feature extraction over Cepstrum-based and PCA-based feature extraction in terms of successful ...

All these methods aim to remove redundant and irrelevant features so that classification of new instances will be more accurate. A popular source of data is ...

Dec 1, 2013 · The results show consistently superior performance of SDF-based feature extraction over Cepstrum-based and PCA-based feature extraction in terms ...