In classifier (or regression) fusion, the aim is to combine the outputs of several algorithms to
boost overall performance. Standard supervised fusion algorithms often require accurate …

Aggregation function is an important component in an information aggregation or
information fusion system. Interrelationships usually exist between the input arguments (eg …

In remote sensing, each sensor can provide complementary or reinforcing information. It is
valuable to fuse outputs from multiple sensors to boost overall performance. Previous …

Classifier fusion methods integrate complementary information from multiple classifiers or
detectors and can aid remote sensing applications such as target detection and …

In many remote sensing and hyperspectral image analysis applications, precise ground truth
information is unavailable or impossible to obtain. Imprecision in ground truth often results …

Target detection is a paramount task in remote sensing which aims to detect points of
interest from a set of data. A crucial aspect attributed to the success of target detection …

The paper shows the possibility of applying the tool of non-additive measures and the belief
functions theory to solving a number of problems of significance analysis and conflict of the …

Aided target detection in infrared data has proven an important area of investigation for both
military and civilian applications. While target detection at the object or pixel-level has been …