Many sensor network applications are data-centric, and data analysis plays an important role in these applications. However, it is a challenging task to find out what specific prob...
We study the potential benefits to classification prediction that arise from having access to unlabeled samples. We compare learning in the semi-supervised model to the standard, ...
Spectral unmixing is an important task for remotely sensed hyperspectral data exploitation. Linear spectral unmixing relies on two main steps: 1) identification of pure spectral c...
Mobile phones have evolved from devices that are just used for voice and text communication to platforms that are able to capture and transmit a range of data types (image, audio, ...
Real-life data mining applications are interesting because they often present a different set of problems for data miners. One such real-life application that we have done is on t...